Curious..about data

Budgeting for SQL Saturdays

We’ve been doing SQLSaturdays for eight years at Louisville now. We’ve had a quite a wide range of budgets depending on the year – a good year (our highest was 2013) and lowest, the first year we started, 2009.

As main organizer, handling the dollars and making sure I spend them right has been an interesting, learning experience for me. For the past two years I’ve had additional help from others on the organizing committee, but for a good six years it was just me doing it and figuring out the do’s and don’ts the hard way. Below is how I do it now, and I have got it down to a good formula that works most of the time.

I divide the revenue into two buckets: – 1 Predictable and 2 Non- predictable. Predictable revenue is what comes in two months before the event. That includes committed sponsors. So far, we have been lucky in getting two or more this way. Non- predictable revenue is what comes in closer to the event, includes last- minute sponsors and revenue based on pre-cons.

Expenses wise – I divide my expenses into the following three buckets.

1. Essentials – These – include event rental, event insurance, and food. Without these,we cannot run.the event. The predictable sponsor revenue goes towards this category of expenses.

2. Wants – After we pass survival, the second bucket of expenses comes in: – that includes speaker dinner, speaker gifts,volunteer shirts; printing of various event- related material like internal signage , event schedule, speaker and event feedback forms; speedpass for speakers;lanyards and nametags. Printing of materials does not cost much. Volunteer-shirts is something we do every year as they are popular not expensive either. The main costs here are speaker dinner and speaker gifts – how much is spent on them depends strongly on how well we are funded.

3. Nice-to- haves – This includes attendee swag/give aways,extra treats to eat (such as cake or ice cream), and reusable event inventory that we can store for future events. We have done lots of cool things in this category – especially with reusable stuff. Our stock includes signage (external to the building), extension cords, foldable garbage bins, raffle boxes, dollies, a laser printer and many smaller items like paper, duct tape, staplers, scissors, and so on. We have enough stuff to just walk in somewhere and set up any event at short notice.

So that said, what about some real numbers? Below is the percentage breakup I have for a good event (where we have had great funding), and a low- funded event.

budgets

It is interesting to see that essentials take up 80% of funding on a typical bad year. Needless to say that nice-to-have-es are are almost down to zero. The question this type of analysis helps me answer is:

What is the minimum $ needed to put up an event?

Every SQL Saturday organizer should absolutely know the answer to this, if not you are walking blind. To know it you have to focus on what are the costs of essentials – room rental and food Remember that both costs are driven by attendee count. For us in Louisville – it is seriously hard to find a free location any more. We don’t like to cut down on attendees as we have worked hard to build up that number and do not like disappointing them. I realize that there are events that can play with this number and reduce the number of attendees to support their funds, but I’d not like to do that unless am absolutely forced to. Finding a free location is also possible with smaller attendee counts, so that is not something to be ruled out entirely, but we’d like to keep that up as much as we can. With attendee count at 200-250, – the other numbers I focus on are as follows.

We have typically six tracks, with six timeslots, adding up to 36 speakers, ideally. For a short -funded event we can cut this down to four tracks with five timeslots, adding upto 20 speakers. This also saves us money on number of rooms rented. We can go from a buffet to a boxed lunch, that costs about 6$-8$ per head. Since 30-40% of people who eat are speakers/sponsors and volunteers, that can significantly reduce my costs too. Given that my costs add up to approx. $800 (rental + insurance) + $1800 (food) + $400$ extra = $3000$ to run a decent event (that includes lunch fees). With less money than that, I would think very hard about doing it. I can, if I find a free location which means even fewer rooms and consequently fewer attendees, but hopefully will not need to. This number gives me a lot of relief when it comes to what to expect by way of funding. It is the same math that goes into what is needed to pull off a pre-con too – if the attendee count does not add up to paying for rooms, lunch, and a minimum of 20% leftover, we typically cancel as it is not worth the costs.

My costs in the ‘want’ bucket are significantly lower with each year because of the reusable inventory swag we have built over years. I would strongly encourage all organizers to invest in this, especially when your funding is good. I do not deny that there is a storage cost that may be involved. We are fortunate to have a volunteer store it at her home for us – but this might be hard for some people. It does, however, help you make your event as mobile as possible without depending on specific locations, and also significantly cuts down on your costs, while keeping up the good appearance of a professionally run event.

Statistics with TSQL and R: Chi Square Test

As I move on from descriptive and largely univariate (one variable based) analysis of data into more multivariate data – one of the first data analysis tests that came to mind is the Chi Square Test. It is a very commonly used test to understand relationships between two variables that are largely categorical in nature. The Chi Square test is often used in clinical trials or experiments that have a before and after analysis of their subjects needed.

For my purpose I downloaded a dataset from here – this is a study of lung conditions and respiratory illnesses among a group of children in Austria. There are many categories here of the conditions these kids were subject to. I summarized the data for my chi square test – and I get a small dataset as below of kids who had a parent who smoked in the home and who were sick. So my two categorical variables are – parent who smoked and did not, and kids who are sick and not. The frequencies I pulled are as below –

Exposure	Sick	Notsick
YES	250	323
NO	401	575

I created a table as below and put the data into it.

CREATE TABLE [dbo].[Respdisease_summary](
 [Exposure] [varchar](5) NULL,
 [Sick] [decimal](18, 2) NULL,
 [Notsick] [decimal](18, 2) NULL
) ON [PRIMARY]

For any dataset to lend itself to the Chi Square test it has to fit the following conditions –

1 Both variables are categorical (in this case – exposure to smoking – yes/no, and health condition – sick/not sick are both categorical).
2 Researchers used a random sample to collect data.
3 Researchers had an adequate sample size.Generally the sample size should be at least 100.
4 The number of respondents in each cell should be at least 5.

My dataset appears to fit these conditions, so I proceeded with analysing the data. Step 1 :Now that I have the data , I need to come up with a statement of what am trying to establish by doing these tests. Or in other words , a hypothesis. In statistical terms the logic is the similar to ‘innocent until proven guilty’ . Or in other words, my hypothesis in this case is that there is no correlation between parents who smoke at home and kids who suffer respiratory illness. My goal is to find out if this is true with 95% certainity(another common standard is what percentage of certainity, also called level of confidence)

Step 2: Next, I need to come up with degrees of freedom for this grid of data. Degrees of freedom in a nutshell means how many cells/data elements are actually independant versus how many are dependant on the one or ones already filled. A detailed discussion on this concept can be found here. You don’t have to understand it in a lot of detail but just enough to use the simple formula –
DF = (# of rows – 1) * (# of columns – 1). In this case – it is (2-1)*(2-1) which is actually 1.

Step 3: I need to create a table of expected values of illness, as opposed to exposed which we got from the data.By that I mean what would value be if the kid was not exposed to the condition – or if our hypothesis that there is no connection just happened to be true?

For each cell in my data, the expected value for each cell of data – is the (row total/sum of all cells)*column total for the cell. I know am using excel like terms here but it is only to make the concept simple. (It is very possible to do this in excel by the way, but am restricting my scope to TSQL and R).

Step 4: Once I get the table of exposed and expected – i need to compare both and arrive at the chi-square value – which is (square of sum (exposed-expected))/sum(expected). Whether I choose to do this on each cell or add all the exposed and expected cell values and calculate it once – really does not matter.

Step 5: After I get the value of chi squared – I can use a table to get the probability of the two variables being correlated, given this chi square value. If you use R it will do this additional step for you and give you the p-value, or probablity as it is called. With other tools you may have to use a calculator like here. If the p value <= 0.05 (which comes fsrom our 95% confidence interval), the value is statistically significant and the null hypothesis is valid. If not, as it is in our case – where the value is 0.3274 – there is no statistically significant correlation for the null hypothesis. So it is safe to conclude that the opposite may be true with 95 percent certainity.

Now, on to the 3 ways of achieving this :

TSQL – I have not used the most optimal T-SQL here. The goal is clarity and I have taken a very methodical step-by-step approach.

CREATE TABLE #expected 
 (Exposure varchar(5), sick decimal(18,4), notsick decimal(18, 4))
 INSERT INTO #expected
 SELECT 'Yes', (A.Row1Total/E.Totalkids)*B.Col1Total as ExpectedSick,
 (A.Row1Total/E.Totalkids) * c.Col2Total as ExpectedNotsick
 FROM 
 (SELECT sick+notsick AS Row1Total FROM [dbo].[Respdisease_summary] where exposure = 'Yes') as A,
 (SELECT sum(sick) AS Col1Total FROM [dbo].[Respdisease_summary]) as b,
 (SELECT sum(notsick) AS Col2Total FROM [dbo].[Respdisease_summary]) as c,
 (SELECT sum(sick) + sum(notsick) AS Totalkids FROM [dbo].[Respdisease_summary]) AS E

INSERT INTO #expected
 SELECT 'No', (D.Row2Total/E.Totalkids)*B.Col1Total
 , (D.Row2Total/E.Totalkids) * c.Col2Total
 FROM 
 (SELECT sum(sick) AS Col1Total FROM [dbo].[Respdisease_summary]) as b,
 (SELECT sum(notsick) AS Col2Total FROM [dbo].[Respdisease_summary]) as c,
 (SELECT sum(sick) + sum(notsick) AS Totalkids FROM [dbo].[Respdisease_summary]) AS E,
 (SELECT sick+notsick AS Row2Total FROM [dbo].[Respdisease_summary] WHERE exposure = 'No') as D

SELECT SQUARE(a.actual-b.expected)/b.expected FROM 
 (SELECT sum(sick+notsick) as actual FROM [dbo].[Respdisease_summary]) A,
 (SELECT SUM(sick+notsick) as expected FROM #expected) B

CREATE TABLE #chisquare 
 (Exposure varchar(5), sick decimal(18,4), notsick decimal(18, 4))

INSERT INTO #chisquare
 SELECT 'yes',square(A.actualsick-B.expectedsick)/B.expectedsick,square(C.actualnotsick-D.expectednotsick)/D.expectednotsick 
 FROM
 (SELECT sick as Actualsick FROM [dbo].[Respdisease_summary] where exposure = 'Yes') as A,
 (SELECT sick as Expectedsick FROM [dbo].[#expected] where exposure = 'Yes') as B,
(SELECT notsick as Actualnotsick FROM [dbo].[Respdisease_summary] where exposure = 'Yes') as C,
 (SELECT notsick as Expectednotsick FROM [dbo].[#expected] where exposure = 'Yes') as D

INSERT INTO #chisquare
 SELECT 'No',square(A.actualsick-B.expectedsick)/B.expectedsick,square(C.actualnotsick-D.expectednotsick)/D.expectednotsick 
 FROM
 (SELECT sick as Actualsick FROM [dbo].[Respdisease_summary] where exposure = 'No') as A,
 (SELECT sick as Expectedsick FROM [dbo].[#expected] where exposure = 'No') as B,
 (SELECT notsick as Actualnotsick FROM [dbo].[Respdisease_summary] where exposure = 'No') as C,
 (SELECT notsick as Expectednotsick FROM [dbo].[#expected] where exposure = 'No') as D

SELECT SUM(sick) + sum(notsick) As CHISQUARE FROM #chisquare

The result I got was as below – a chi square value of 0.9590. If I look up the calculator for this chi square value with 1 degree of freedom – I get a probability of 0.3274.

chisqtsql

R: It is with problems like this that you really get to appreciate the efficiency of R. Just two little steps, easy-peasy and you get all that went into those multiple lines of TSQL code.

#Install basic packages
install.packages("RODBC")
library(RODBC)
#Connect to server and retrieve data
cn <- odbcDriverConnect(connection="Driver={SQL Server Native Client 11.0};server=MALATH-PC\\SQL01;database=WorldHealth;Uid=sa;Pwd=<mypwd>")
data1 <- sqlQuery(cn, ' select Sick,Notsick from dbo.Respdisease_summary')
#Calculate the chi square value
chisqt<-chisq.test(data1[1:2,c("Sick","Notsick")],correct=FALSE)
chisqt

I get results as below – R neatly does the calculation of P-value too for us.

chisqr

3 R Code from within of TSQL. This is my favorite part. Now you can tap into what R does from within of TSQL itself with a few simple lines of code as below.

EXEC sp_execute_external_script
 @language = N'R'
 ,@script = N'x<-chisq.test(InputDataSet[1:2,c("Sick","Notsick")], correct = FALSE);print(x)'
 ,@input_data_1 = N'SELECT Sick,Notsick FROM [WorldHealth].[dbo].[Respdisease_summary]'

And bingo, same results as 2.

chisqrtsql

There is a correction called Yates continuity correction that sometimes needs to be applied if our degrees of freedom is just one. R by default uses this coefficient which text book wise is jus t subtracting 0.5 from expected values. But for some reason I could not get the values to tie up using manual math/tsql and R upon usage of this, so I turned it off by saying ‘correct = False’ in R statement. It is also noteworthy that Chi SQuare test tells you nothing about the actual relationship between variables – it is only a test of independance and can tell you about degree of dependancy , that is all.

Statistics with T-SQL and R – the Pearson’s Correlation Coefficient

In this post I will attempt to explore calculation of a very basic statistic based on linear relationship between two variables. That is, a number that tells you if two numeric variables in a dataset are possibly correlated and if yes, by what degree. The Pearson’s coefficient is a number that attempts to measure this relationship.

The dataset I am using for this is downloaded from here. It is a dataset related to gender development index from various parts of the world. I am not using all the variables here. I am only attempting to examine if there is a correlation between average number of years in school, and gross national income, for women. Or in other words – Do women stay longer or shorter in schools because of income reasons? One important thing to be aware as we study this – is that correlation does not mean causation. By that – if I find a correlation between number of years women spend in school and the income, does not really mean the two are directly related. There may be many other factors influencing this relationship – or, after studying all the other factors we may very well conclude that there is not a significant relationship one way or the other. But, it is a starting point to see if there is any correlation between these two variables across countries.

The statistical definition of Pearson’s R Coefficient, as it is called, can be found in detail here for those interested. A value of 1 indicates that there is a strong positive correlation(the two variables in question increase together), 0 indicates no correlation between them, and -1 indicates a strong negative correlation (the two variables decrease together). But you rarely get a perfect -1, 0 or 1. Most values are fractional and interpreted as follows:
High correlation: .5 to 1.0 or -0.5 to 1.0.
Medium correlation: .3 to .5 or -0.3 to .5.
Low correlation: .1 to .3 or -0.1 to -0.3.

Now, let us look at calculation this value for the two variables we have chosen using R, then T-SQL and then R script within T-SQL.
Using R:

install.packages(“RODBC”)
library(RODBC)
mydata <- sqlQuery(cn, ‘select [FemaleMeanYearsofSchooling2014],
[GNAPerCapitaWomen2014]
FROM [WorldHealth].[dbo].[GenderDevelopmentIndex] WHERE [femalemeanyearsofschooling2014] >0 ‘)

cor(mydata)

R creates a matrix out the two columns of data and correlates it four ways. I have only highlighted what is relevant to us – a value of 0.64, which suggests a moderately strong correlation.

The same calculation can be done with T-SQL. It is not as simple or elegant as it is in R, but it is very doable. To understand the formula read here. Although it is very possible to do this in one step, I have broken it up into 4 steps to help with clarity and understanding.

TSQL Code:

DECLARE @PART1 FLOAT, @PART2 FLOAT, @PART3 FLOAT, @PART4 FLOAT
SELECT @PART1 = SUM([FemaleSchoolingyears2014]*[GNAPerCapitaWomen2014])
FROM [dbo].[GenderDevelopmentIndex] where [FemaleSchoolingyears2014] > 0

SELECT @PART2 = (SUM([FemaleSchoolingyears2014])*SUM([GNAPerCapitaWomen2014]))/count(*)
FROM [dbo].[GenderDevelopmentIndex] where [FemaleSchoolingyears2014] > 0

SELECT @PART3 = SQRT(SUM([FemaleSchoolingyears2014]*[FemaleSchoolingyears2014])
– (SUM([FemaleSchoolingyears2014])*SUM([FemaleSchoolingyears2014]))/count(*))
FROM [dbo].[GenderDevelopmentIndex] where [FemaleSchoolingyears2014] > 0

SELECT @PART4 = SQRT(SUM([GNAPerCapitaWomen2014]*[GNAPerCapitaWomen2014])
– (SUM([GNAPerCapitaWomen2014])*SUM([GNAPerCapitaWomen2014]))/count(*))
FROM [dbo].[GenderDevelopmentIndex] where [FemaleSchoolingyears2014] > 0

SELECT ‘Pearsons correlation coefficient=’,ROUND((@PART1-@PART2)/(@PART3*@PART4), 2)

The results I get are as below:

cor-TSQL

So far, in both cases the value is a good 0.64. Now , instead of performing all this math in T-SQL we can call the R function to do it in one line, within T-SQL.

R call from within T-SQL:

EXEC sp_execute_external_script
@language = N’R’
,@script = N’ cor <-cor(InputDataSet$FemaleMeanYearsofSchooling2014,InputDataSet$GNAPerCapitaWomen2014);
print(cor);’
,@input_data_1 = N’select FemaleMeanYearsofSchooling2014,GNAPerCapitaWomen2014 FROM [WorldHealth].[dbo].[GenderDevelopmentIndex] where [FemaleSchoolingyears2014] > 0
;’;

My results are as below:

cor-r-tsql

As we can see, we got the same results in all 3 cases. The 0.64 correlation indicates the possibility of a moderately strong correlation between length of years women are in school and the GDP ratio of the country. It does not mean the GDP factor is the cause but merely a possibility. There is a old post authored by Joe Celko here that refers to the same calculation and can also help with conceptual understanding.

Thanks for reading.

Script for creating test data for odds ratio

Make sure you have a working version of SQL Server 2016.

USE [master]
GO

/****** Object: Database [WorldHealth] ******/
CREATE DATABASE [WorldHealth]
CONTAINMENT = NONE
ON PRIMARY
( NAME = N’WorldHealth’, FILENAME = N’D:\Microsoft SQL Server\DATA\WorldHealth.mdf’ , SIZE = 8192KB , MAXSIZE = UNLIMITED, FILEGROWTH = 65536KB )
LOG ON
( NAME = N’WorldHealth_log’, FILENAME = N’D:\Microsoft SQL Server\\WorldHealth_log.ldf’ , SIZE = 8192KB , MAXSIZE = 2048GB , FILEGROWTH = 65536KB )
GO

CREATE TABLE [dbo].[smokers](
[Smokingstatus] [char](1) NULL,
[AgeRange] [varchar](50) NULL,
[HealthyorSick] [char](1) NULL,
[Numberofpeople] [int] NULL
) ON [PRIMARY]

GO
INSERT [dbo].[smokers] ([Smokingstatus], [AgeRange], [HealthyorSick], [Numberofpeople]) VALUES (N’0′, N’ 1′, N’1′, 20132)
GO
INSERT [dbo].[smokers] ([Smokingstatus], [AgeRange], [HealthyorSick], [Numberofpeople]) VALUES (N’0′, N’ 2′, N’1′, 21671)
GO
INSERT [dbo].[smokers] ([Smokingstatus], [AgeRange], [HealthyorSick], [Numberofpeople]) VALUES (N’0′, N’ 3′, N’1′, 19790)
GO
INSERT [dbo].[smokers] ([Smokingstatus], [AgeRange], [HealthyorSick], [Numberofpeople]) VALUES (N’0′, N’ 4′, N’1′, 16499)
GO
INSERT [dbo].[smokers] ([Smokingstatus], [AgeRange], [HealthyorSick], [Numberofpeople]) VALUES (N’1′, N’ 1′, N’1′, 39990)
GO
INSERT [dbo].[smokers] ([Smokingstatus], [AgeRange], [HealthyorSick], [Numberofpeople]) VALUES (N’1′, N’ 2′, N’1′, 32894)
GO
INSERT [dbo].[smokers] ([Smokingstatus], [AgeRange], [HealthyorSick], [Numberofpeople]) VALUES (N’1′, N’ 3′, N’1′, 20739)
GO
INSERT [dbo].[smokers] ([Smokingstatus], [AgeRange], [HealthyorSick], [Numberofpeople]) VALUES (N’1′, N’ 4′, N’1′, 11197)
GO
INSERT [dbo].[smokers] ([Smokingstatus], [AgeRange], [HealthyorSick], [Numberofpeople]) VALUES (N’0′, N’ 1′, N’0′, 204)
GO
INSERT [dbo].[smokers] ([Smokingstatus], [AgeRange], [HealthyorSick], [Numberofpeople]) VALUES (N’0′, N’ 2′, N’0′, 394)
GO
INSERT [dbo].[smokers] ([Smokingstatus], [AgeRange], [HealthyorSick], [Numberofpeople]) VALUES (N’0′, N’ 3′, N’0′, 488)
GO
INSERT [dbo].[smokers] ([Smokingstatus], [AgeRange], [HealthyorSick], [Numberofpeople]) VALUES (N’0′, N’ 4′, N’0′, 766)
GO
INSERT [dbo].[smokers] ([Smokingstatus], [AgeRange], [HealthyorSick], [Numberofpeople]) VALUES (N’1′, N’ 1′, N’0′, 647)
GO
INSERT [dbo].[smokers] ([Smokingstatus], [AgeRange], [HealthyorSick], [Numberofpeople]) VALUES (N’1′, N’ 2′, N’1′, 857)
GO
INSERT [dbo].[smokers] ([Smokingstatus], [AgeRange], [HealthyorSick], [Numberofpeople]) VALUES (N’1′, N’ 3′, N’1′, 855)
GO
INSERT [dbo].[smokers] ([Smokingstatus], [AgeRange], [HealthyorSick], [Numberofpeople]) VALUES (N’1′, N’ 4′, N’0′, 643)
GO

TSQL Tuesday #081 – Sharpening something

SqlTuesday

This TSQL tuesday is hosted by my good friend Jason Brimhall – Jason has put forth a creative challenge – plan to do something, carry out that plan, and then write about the experience. He gave a two week period between planning and implementation. I must confess that i cheated a bit here, because what am writing about is not really a two week thing – but it is an opportunity for me to write on something I recently planned and carried out.
I have about a decade and a half of operational DBA experience as of this year. I was beginning to tire of the relentless repetitive nature of the work, and longed to do something different. I was reading a lot on BI/Analytics – although I have little background in BI – I was fascinated by what was currently possible with many tools available to analyze data and come up with interesting findings. I love painting dashboards, and I have a background in statistics as well. Talking to a few people in the community – it seemed to make sense to find my way into BI/Analytics. But here was was the catch. What was the industry to go into? Analytics is very industry specific – knowledge of data and its nuances being as important as knowledge of technical tools one dabbles with. Some thought and deliberation seemed to point to healthcare analytics as a good choice. So, I had a plan. To find a job that introduces me to the wide world of BI/healthcare analytics, and learn it as much as I can on my own.
After a 3 month search that involved many uncertainities and turning down many lucrative operational dba offers – I found a job where they actually needed a BI DBA – they were willing to let me learn BI if I brought my DBA skills to the table. They were also going into Tableau and analytics. And what is more, they do healthcare.
I took the job and then started working on upping my skills in the said area. I’ve joined a course in healthcare analytics. I use pluralsight to learn SQL Server BI, and udemy for R programming. I also blog once a week on something i learned with R on healthcare data. My blogging interest and following has picked up considerably.
That is in short, my mid life career transition – a rather big subject for a TSQL tuesday, but one that most people run into. I wish you best of luck – with patience and perseverance to find what you truly love to do. Thanks Jason, for the opportunity.

Descriptive Statistics with SQL and R – II

In the previous post I looked into some very basic and common measures of descriptive statistics – mean, median and mode, and how to derive these using T-SQL, R as well as a combo of the two in SQL Server 2016. These measures also called measures of ‘Central Tendency‘. In this post am going to describe some measures called ‘Measures of Dispersion‘. Dispersion refers to how much the said value differs from the average and how many such values are distributed around the average.

Below are 4 very common measures of dispersion –

Range
Inter-Quartile Range
Variance
Standard Deviation

The first and most common measure of dispersion is called ‘Range‘. The range is just the difference between the maximum and minimum values in the dataset. It tells you how much gap there is between the two and therefore how wide the dataset is in terms of its values. It is however, quite misleading when you have outliers in the data. If you have one value that is very large or very small that can skew the Range and does not really mean you have values spanning the minimum to the maximum.

To lower this kind of an issue with outliers – a second variation of the range called Inter-Quartile Range, or IQR is used. The IQR is calculated by dividing the dataset into 4 equal parts after sorting the said value in ascending order. For the first and third part, the maximum values are taken and then subtracted from each other. The IQR ensures that you are looking at top and near-bottom ranges and therefore the value it gives is probably spanning the range.

A more accurate calculation of dispersion is called Variance. Variance is the average of the difference between each value and the mean, divided by the number of values. When your dataset is comprised of an entire population the number of values are the total number of values, but when it is comprised of a sample, the number of values are deducted by 1 to ensure a statistical adjustment. The larger the variance, the more widespread the values are.

The last measure of dispersion am going to look into in this post is Standard Deviation.The Standard Deviation is the square root of the variance. The smaller the standard deviation, the lesser is the dispersion around the mean. The larger, the greater.

The higher the values of variance and standard deviation – the more skewed your data is and the less likely it is to lend itself to any real statistical analysis or even forecasting or predictive reporting.

I used the same data set that I did in the earlier post to run queries for this. Details on that can be found here.

Using T-SQL:

Below are my T-SQL queries to derive range, inter quartile range, variance and standard deviation. I was surprised to find that T-SQL actually has a built in function for variance, which makes it very easy. Was not sure why this particular function would exist when the vast majority of other statistical functions don’t, but makes sense to use it since it does 🙂

–Calculate range of the dataset
SELECT MAX(AGE) – MIN(AGE) as Range FROM [dbo].[WHO_LifeExpectancy]

–Calculate Interquartile range of the dataset
SELECT MAX(QUARTILEMAX) – MIN(QUARTILEMAX) AS INTERQUARTILERANGE
FROM
(SELECT QUARTILE, MAX(AGE) AS QUARTILEMAX FROM (SELECT NTILE(4) OVER ( ORDER BY Age ) AS Quartile ,
Age FROM [dbo].[WHO_LifeExpectancy]) A
GROUP BY QUARTILE HAVING QUARTILE = 1 OR QUARTILE = 3) A

–Calculate variance of the datasest
SELECT VAR(Age) AS VARIANCE FROM [dbo].[WHO_LifeExpectancy]

–Calculate standard deviation of the dataset
SELECT SQRT(VAR(Age)) AS STDDEV FROM [dbo].[WHO_LifeExpectancy]

Results are as below:

descstats2

Using R:

The R script to do the exact same thing is as below. None of these calculations require anything more than calling a packaged function in R, which is why it is usually the preferred way to do it.

#load necessary libraries and connect to the database
install.packages(“RODBC”)
library(RODBC)

cn <- odbcDriverConnect(connection=”Driver={SQL Server Native Client 11.0};server=MALATH-PC\\SQL01;database=WorldHealth;Uid=sa;Pwd=<password>”)
data <- sqlQuery(cn, ‘select age from [dbo].[WHO_LifeExpectancy] where age is not null’)

#Get range
agerange <- max(data)-min(data)
agerange

#Get Interquartile Range
interquartileagerange <- IQR(unlist(data))
interquartileagerange

#Get Variance
variance <- var(data)
variance

#Get Standard Deviation
stddev <- sd(unlist(data))
stddev

The results you get, almost exact matches to what T-SQL gave us:

descstats2-R

3. Using R function calls with T-SQL

Now the last part , where we call the R script via T-SQL. We have to make small changes to the script – the ‘cat’ function to concatenate results, /n to introduce a carriage return for readability and removing the ‘unlist’ that native R needs because of how R structures data it reads directly from SQL . But for this the math is exactly the same.

— calculate simple dispersion measures
EXEC sp_execute_external_script
@language = N’R’
,@script = N’ range <-max(InputDataSet$LifeExpectancies)-min(InputDataSet$LifeExpectancies)
cat(“Range”, range,”\n”);
InterquartileRange <-IQR(InputDataSet$LifeExpectancies)
cat(“InterQuartileRange”, InterquartileRange,”\n”);
variance <-var(InputDataSet$LifeExpectancies)
cat(“Variance”, variance,”\n”);
stdeviation <-sd(InputDataSet$LifeExpectancies)
cat(“StdDeviation”, stdeviation,”\n”);’
,@input_data_1 = N’SELECT LifeExpectancies = Age FROM [WorldHealth].[dbo].[WHO_LifeExpectancy];’
;

And the results, exactly the same as the two above:

descstats2-sqlandr

It has been fun so far doing this in 3 different ways and getting the same results. But as we go into more advanced statistics it will not be that simple. It will, however, definitely help us understand how far we can push statistical math with T-SQL, how easy and simple it is with R, and what can/cannot be done in the first version of calling R from within T-SQL. I can’t wait to play with it further and blog as I go along.

Thank you for reading.

Script to create demo database and load data for statistics and R

Make sure you have a working install of SQL Server 2016. The size of the database is only 8 MB.

USE [master]
GO

/****** Object: Database [WorldHealth] Script Date: 7/15/2016 4:44:58 PM ******/
CREATE DATABASE [WorldHealth]
CONTAINMENT = NONE
ON PRIMARY
( NAME = N’WorldHealth’, FILENAME = N’D:\DATA\WorldHealth.mdf’ , SIZE = 8192KB , MAXSIZE = UNLIMITED, FILEGROWTH = 65536KB )
LOG ON
( NAME = N’WorldHealth_log’, FILENAME = N’D:\Log\WorldHealth_log.ldf’ , SIZE = 8192KB , MAXSIZE = 2048GB , FILEGROWTH = 65536KB )
GO

ALTER DATABASE [WorldHealth] SET COMPATIBILITY_LEVEL = 130
GO

USE [WorldHealth]
GO
/****** Object: Table [dbo].[WHO_LifeExpectancy] Script Date: 7/15/2016 4:41:49 PM ******/
SET ANSI_NULLS ON
GO
SET QUOTED_IDENTIFIER ON
GO
SET ANSI_PADDING ON
GO
CREATE TABLE [dbo].[WHO_LifeExpectancy](
[Country] [varchar](50) NULL,
[Year] [varchar](50) NULL,
[Gender] [varchar](50) NULL,
[Age] [numeric](18, 2) NULL
) ON [PRIMARY]

GO
SET ANSI_PADDING OFF
GO
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Afghanistan’, N’2000′, N’Male’, CAST(45.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Albania’, N’2000′, N’Male’, CAST(61.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Algeria’, N’2000′, N’Male’, CAST(61.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Angola’, N’2000′, N’Male’, CAST(38.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Antigua and Barbuda’, N’2000′, N’Male’, CAST(63.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Argentina’, N’2000′, N’Male’, CAST(62.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Armenia’, N’2000′, N’Male’, CAST(61.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Australia’, N’2000′, N’Male’, CAST(67.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Austria’, N’2000′, N’Male’, CAST(66.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Azerbaijan’, N’2000′, N’Male’, CAST(57.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Bahamas’, N’2000′, N’Male’, CAST(61.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Bahrain’, N’2000′, N’Male’, CAST(64.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Bangladesh’, N’2000′, N’Male’, CAST(56.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Barbados’, N’2000′, N’Male’, CAST(63.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Belarus’, N’2000′, N’Male’, CAST(57.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Belgium’, N’2000′, N’Male’, CAST(65.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Belize’, N’2000′, N’Male’, CAST(58.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Benin’, N’2000′, N’Male’, CAST(47.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Bhutan’, N’2000′, N’Male’, CAST(53.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Bolivia (Plurinational State of)’, N’2000′, N’Male’, CAST(54.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Bosnia and Herzegovina’, N’2000′, N’Male’, CAST(62.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Botswana’, N’2000′, N’Male’, CAST(42.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Brazil’, N’2000′, N’Male’, CAST(59.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Brunei Darussalam’, N’2000′, N’Male’, CAST(66.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Bulgaria’, N’2000′, N’Male’, CAST(60.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Burkina Faso’, N’2000′, N’Male’, CAST(42.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Burundi’, N’2000′, N’Male’, CAST(41.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Cote d”Ivoire’, N’2000′, N’Male’, CAST(41.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Cabo Verde’, N’2000′, N’Male’, CAST(60.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Cambodia’, N’2000′, N’Male’, CAST(42.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Cameroon’, N’2000′, N’Male’, CAST(43.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Canada’, N’2000′, N’Male’, CAST(68.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Central African Republic’, N’2000′, N’Male’, CAST(39.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Chad’, N’2000′, N’Male’, CAST(39.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Chile’, N’2000′, N’Male’, CAST(65.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’China’, N’2000′, N’Male’, CAST(63.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Colombia’, N’2000′, N’Male’, CAST(59.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Comoros’, N’2000′, N’Male’, CAST(50.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Congo’, N’2000′, N’Male’, CAST(45.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Costa Rica’, N’2000′, N’Male’, CAST(66.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Croatia’, N’2000′, N’Male’, CAST(63.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Cuba’, N’2000′, N’Male’, CAST(66.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Cyprus’, N’2000′, N’Male’, CAST(67.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Czech Republic’, N’2000′, N’Male’, CAST(63.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Democratic People”s Republic of Korea’, N’2000′, N’Male’, CAST(55.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Democratic Republic of the Congo’, N’2000′, N’Male’, CAST(42.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Denmark’, N’2000′, N’Male’, CAST(66.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Djibouti’, N’2000′, N’Male’, CAST(49.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Dominican Republic’, N’2000′, N’Male’, CAST(61.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Ecuador’, N’2000′, N’Male’, CAST(61.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Egypt’, N’2000′, N’Male’, CAST(58.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’El Salvador’, N’2000′, N’Male’, CAST(54.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Equatorial Guinea’, N’2000′, N’Male’, CAST(45.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Eritrea’, N’2000′, N’Male’, CAST(34.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Estonia’, N’2000′, N’Male’, CAST(59.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Ethiopia’, N’2000′, N’Male’, CAST(42.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Fiji’, N’2000′, N’Male’, CAST(59.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Finland’, N’2000′, N’Male’, CAST(65.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’France’, N’2000′, N’Male’, CAST(67.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Gabon’, N’2000′, N’Male’, CAST(51.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Gambia’, N’2000′, N’Male’, CAST(48.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Georgia’, N’2000′, N’Male’, CAST(61.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Germany’, N’2000′, N’Male’, CAST(66.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Ghana’, N’2000′, N’Male’, CAST(49.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Greece’, N’2000′, N’Male’, CAST(67.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Grenada’, N’2000′, N’Male’, CAST(60.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Guatemala’, N’2000′, N’Male’, CAST(53.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Guinea’, N’2000′, N’Male’, CAST(45.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Guinea-Bissau’, N’2000′, N’Male’, CAST(44.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Guyana’, N’2000′, N’Male’, CAST(55.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Haiti’, N’2000′, N’Male’, CAST(49.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Honduras’, N’2000′, N’Male’, CAST(60.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Hungary’, N’2000′, N’Male’, CAST(60.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Iceland’, N’2000′, N’Male’, CAST(69.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’India’, N’2000′, N’Male’, CAST(53.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Indonesia’, N’2000′, N’Male’, CAST(58.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Iran (Islamic Republic of)’, N’2000′, N’Male’, CAST(61.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Iraq’, N’2000′, N’Male’, CAST(59.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Ireland’, N’2000′, N’Male’, CAST(65.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Israel’, N’2000′, N’Male’, CAST(68.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Italy’, N’2000′, N’Male’, CAST(68.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Jamaica’, N’2000′, N’Male’, CAST(62.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Japan’, N’2000′, N’Male’, CAST(70.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Jordan’, N’2000′, N’Male’, CAST(62.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Kazakhstan’, N’2000′, N’Male’, CAST(53.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Kenya’, N’2000′, N’Male’, CAST(44.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Kiribati’, N’2000′, N’Male’, CAST(54.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Kuwait’, N’2000′, N’Male’, CAST(63.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Kyrgyzstan’, N’2000′, N’Male’, CAST(56.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Lao People”s Democratic Republic’, N’2000′, N’Male’, CAST(49.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Latvia’, N’2000′, N’Male’, CAST(58.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Lebanon’, N’2000′, N’Male’, CAST(59.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Lesotho’, N’2000′, N’Male’, CAST(42.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Liberia’, N’2000′, N’Male’, CAST(43.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Libya’, N’2000′, N’Male’, CAST(61.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Lithuania’, N’2000′, N’Male’, CAST(59.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Luxembourg’, N’2000′, N’Male’, CAST(66.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Madagascar’, N’2000′, N’Male’, CAST(49.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Malawi’, N’2000′, N’Male’, CAST(36.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Malaysia’, N’2000′, N’Male’, CAST(62.50 AS Numeric(18, 2)))
GO
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Maldives’, N’2000′, N’Male’, CAST(61.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Mali’, N’2000′, N’Male’, CAST(43.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Malta’, N’2000′, N’Male’, CAST(67.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Mauritania’, N’2000′, N’Male’, CAST(51.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Mauritius’, N’2000′, N’Male’, CAST(61.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Mexico’, N’2000′, N’Male’, CAST(64.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Micronesia (Federated States of)’, N’2000′, N’Male’, CAST(59.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Mongolia’, N’2000′, N’Male’, CAST(54.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Montenegro’, N’2000′, N’Male’, CAST(62.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Morocco’, N’2000′, N’Male’, CAST(59.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Mozambique’, N’2000′, N’Male’, CAST(41.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Myanmar’, N’2000′, N’Male’, CAST(53.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Namibia’, N’2000′, N’Male’, CAST(49.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Nepal’, N’2000′, N’Male’, CAST(54.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Netherlands’, N’2000′, N’Male’, CAST(67.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’New Zealand’, N’2000′, N’Male’, CAST(67.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Nicaragua’, N’2000′, N’Male’, CAST(48.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Niger’, N’2000′, N’Male’, CAST(43.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Nigeria’, N’2000′, N’Male’, CAST(40.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Norway’, N’2000′, N’Male’, CAST(67.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Oman’, N’2000′, N’Male’, CAST(62.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Pakistan’, N’2000′, N’Male’, CAST(54.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Panama’, N’2000′, N’Male’, CAST(64.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Papua New Guinea’, N’2000′, N’Male’, CAST(51.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Paraguay’, N’2000′, N’Male’, CAST(61.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Peru’, N’2000′, N’Male’, CAST(57.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Philippines’, N’2000′, N’Male’, CAST(56.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Poland’, N’2000′, N’Male’, CAST(62.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Portugal’, N’2000′, N’Male’, CAST(65.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Qatar’, N’2000′, N’Male’, CAST(64.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Republic of Korea’, N’2000′, N’Male’, CAST(65.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Republic of Moldova’, N’2000′, N’Male’, CAST(57.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Romania’, N’2000′, N’Male’, CAST(60.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Russian Federation’, N’2000′, N’Male’, CAST(53.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Rwanda’, N’2000′, N’Male’, CAST(35.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Saint Lucia’, N’2000′, N’Male’, CAST(62.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Saint Vincent and the Grenadines’, N’2000′, N’Male’, CAST(61.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Samoa’, N’2000′, N’Male’, CAST(61.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Sao Tome and Principe’, N’2000′, N’Male’, CAST(53.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Saudi Arabia’, N’2000′, N’Male’, CAST(61.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Senegal’, N’2000′, N’Male’, CAST(49.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Serbia’, N’2000′, N’Male’, CAST(62.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Seychelles’, N’2000′, N’Male’, CAST(61.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Sierra Leone’, N’2000′, N’Male’, CAST(33.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Singapore’, N’2000′, N’Male’, CAST(68.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Slovakia’, N’2000′, N’Male’, CAST(61.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Slovenia’, N’2000′, N’Male’, CAST(63.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Solomon Islands’, N’2000′, N’Male’, CAST(58.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Somalia’, N’2000′, N’Male’, CAST(42.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’South Africa’, N’2000′, N’Male’, CAST(48.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’South Sudan’, N’2000′, N’Male’, CAST(41.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Spain’, N’2000′, N’Male’, CAST(66.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Sri Lanka’, N’2000′, N’Male’, CAST(61.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Sudan’, N’2000′, N’Male’, CAST(49.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Suriname’, N’2000′, N’Male’, CAST(57.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Swaziland’, N’2000′, N’Male’, CAST(41.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Sweden’, N’2000′, N’Male’, CAST(68.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Switzerland’, N’2000′, N’Male’, CAST(67.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Syrian Arab Republic’, N’2000′, N’Male’, CAST(60.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Tajikistan’, N’2000′, N’Male’, CAST(53.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Thailand’, N’2000′, N’Male’, CAST(61.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Macedonia’, N’2000′, N’Male’, CAST(62.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Timor-Leste’, N’2000′, N’Male’, CAST(50.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Togo’, N’2000′, N’Male’, CAST(47.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Tonga’, N’2000′, N’Male’, CAST(63.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Trinidad and Tobago’, N’2000′, N’Male’, CAST(59.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Tunisia’, N’2000′, N’Male’, CAST(62.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Turkey’, N’2000′, N’Male’, CAST(59.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Turkmenistan’, N’2000′, N’Male’, CAST(54.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Uganda’, N’2000′, N’Male’, CAST(39.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Ukraine’, N’2000′, N’Male’, CAST(56.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’United Arab Emirates’, N’2000′, N’Male’, CAST(64.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’United Kingdom’, N’2000′, N’Male’, CAST(67.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’United Republic of Tanzania’, N’2000′, N’Male’, CAST(42.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’United States of America’, N’2000′, N’Male’, CAST(65.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Uruguay’, N’2000′, N’Male’, CAST(63.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Uzbekistan’, N’2000′, N’Male’, CAST(57.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Vanuatu’, N’2000′, N’Male’, CAST(60.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Venezuela’, N’2000′, N’Male’, CAST(60.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Viet Nam’, N’2000′, N’Male’, CAST(59.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Yemen’, N’2000′, N’Male’, CAST(52.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Zambia’, N’2000′, N’Male’, CAST(36.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Zimbabwe’, N’2000′, N’Male’, CAST(39.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Afghanistan’, N’2000′, N’Male’, CAST(45.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Albania’, N’2000′, N’Male’, CAST(61.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Algeria’, N’2000′, N’Male’, CAST(61.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Angola’, N’2000′, N’Male’, CAST(38.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Antigua and Barbuda’, N’2000′, N’Male’, CAST(63.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Argentina’, N’2000′, N’Male’, CAST(62.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Armenia’, N’2000′, N’Male’, CAST(61.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Australia’, N’2000′, N’Male’, CAST(67.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Austria’, N’2000′, N’Male’, CAST(66.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Azerbaijan’, N’2000′, N’Male’, CAST(57.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Bahamas’, N’2000′, N’Male’, CAST(61.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Bahrain’, N’2000′, N’Male’, CAST(64.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Bangladesh’, N’2000′, N’Male’, CAST(56.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Barbados’, N’2000′, N’Male’, CAST(63.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Belarus’, N’2000′, N’Male’, CAST(57.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Belgium’, N’2000′, N’Male’, CAST(65.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Belize’, N’2000′, N’Male’, CAST(58.90 AS Numeric(18, 2)))
GO
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Benin’, N’2000′, N’Male’, CAST(47.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Bhutan’, N’2000′, N’Male’, CAST(53.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Bolivia (Plurinational State of)’, N’2000′, N’Male’, CAST(54.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Bosnia and Herzegovina’, N’2000′, N’Male’, CAST(62.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Botswana’, N’2000′, N’Male’, CAST(42.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Brazil’, N’2000′, N’Male’, CAST(59.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Brunei Darussalam’, N’2000′, N’Male’, CAST(66.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Bulgaria’, N’2000′, N’Male’, CAST(60.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Burkina Faso’, N’2000′, N’Male’, CAST(42.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Burundi’, N’2000′, N’Male’, CAST(41.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Cote d”Ivoire’, N’2000′, N’Male’, CAST(41.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Cabo Verde’, N’2000′, N’Male’, CAST(60.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Cambodia’, N’2000′, N’Male’, CAST(42.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Cameroon’, N’2000′, N’Male’, CAST(43.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Canada’, N’2000′, N’Male’, CAST(68.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Central African Republic’, N’2000′, N’Male’, CAST(39.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Chad’, N’2000′, N’Male’, CAST(39.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Chile’, N’2000′, N’Male’, CAST(65.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’China’, N’2000′, N’Male’, CAST(63.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Colombia’, N’2000′, N’Male’, CAST(59.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Comoros’, N’2000′, N’Male’, CAST(50.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Congo’, N’2000′, N’Male’, CAST(45.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Costa Rica’, N’2000′, N’Male’, CAST(66.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Croatia’, N’2000′, N’Male’, CAST(63.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Cuba’, N’2000′, N’Male’, CAST(66.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Cyprus’, N’2000′, N’Male’, CAST(67.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Czech Republic’, N’2000′, N’Male’, CAST(63.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Democratic People”s Republic of Korea’, N’2000′, N’Male’, CAST(55.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Democratic Republic of the Congo’, N’2000′, N’Male’, CAST(42.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Denmark’, N’2000′, N’Male’, CAST(66.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Djibouti’, N’2000′, N’Male’, CAST(49.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Dominican Republic’, N’2000′, N’Male’, CAST(61.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Ecuador’, N’2000′, N’Male’, CAST(61.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Egypt’, N’2000′, N’Male’, CAST(58.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’El Salvador’, N’2000′, N’Male’, CAST(54.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Equatorial Guinea’, N’2000′, N’Male’, CAST(45.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Eritrea’, N’2000′, N’Male’, CAST(34.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Estonia’, N’2000′, N’Male’, CAST(59.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Ethiopia’, N’2000′, N’Male’, CAST(42.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Fiji’, N’2000′, N’Male’, CAST(59.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Finland’, N’2000′, N’Male’, CAST(65.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’France’, N’2000′, N’Male’, CAST(67.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Gabon’, N’2000′, N’Male’, CAST(51.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Gambia’, N’2000′, N’Male’, CAST(48.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Georgia’, N’2000′, N’Male’, CAST(61.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Germany’, N’2000′, N’Male’, CAST(66.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Ghana’, N’2000′, N’Male’, CAST(49.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Greece’, N’2000′, N’Male’, CAST(67.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Grenada’, N’2000′, N’Male’, CAST(60.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Guatemala’, N’2000′, N’Male’, CAST(53.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Guinea’, N’2000′, N’Male’, CAST(45.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Guinea-Bissau’, N’2000′, N’Male’, CAST(44.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Guyana’, N’2000′, N’Male’, CAST(55.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Haiti’, N’2000′, N’Male’, CAST(49.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Honduras’, N’2000′, N’Male’, CAST(60.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Hungary’, N’2000′, N’Male’, CAST(60.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Iceland’, N’2000′, N’Male’, CAST(69.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’India’, N’2000′, N’Male’, CAST(53.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Indonesia’, N’2000′, N’Male’, CAST(58.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Iran (Islamic Republic of)’, N’2000′, N’Male’, CAST(61.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Iraq’, N’2000′, N’Male’, CAST(59.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Ireland’, N’2000′, N’Male’, CAST(65.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Israel’, N’2000′, N’Male’, CAST(68.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Italy’, N’2000′, N’Male’, CAST(68.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Jamaica’, N’2000′, N’Male’, CAST(62.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Japan’, N’2000′, N’Male’, CAST(70.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Jordan’, N’2000′, N’Male’, CAST(62.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Kazakhstan’, N’2000′, N’Male’, CAST(53.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Kenya’, N’2000′, N’Male’, CAST(44.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Kiribati’, N’2000′, N’Male’, CAST(54.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Kuwait’, N’2000′, N’Male’, CAST(63.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Kyrgyzstan’, N’2000′, N’Male’, CAST(56.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Lao People”s Democratic Republic’, N’2000′, N’Male’, CAST(49.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Latvia’, N’2000′, N’Male’, CAST(58.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Lebanon’, N’2000′, N’Male’, CAST(59.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Lesotho’, N’2000′, N’Male’, CAST(42.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Liberia’, N’2000′, N’Male’, CAST(43.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Libya’, N’2000′, N’Male’, CAST(61.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Lithuania’, N’2000′, N’Male’, CAST(59.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Luxembourg’, N’2000′, N’Male’, CAST(66.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Madagascar’, N’2000′, N’Male’, CAST(49.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Malawi’, N’2000′, N’Male’, CAST(36.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Malaysia’, N’2000′, N’Male’, CAST(62.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Maldives’, N’2000′, N’Male’, CAST(61.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Mali’, N’2000′, N’Male’, CAST(43.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Malta’, N’2000′, N’Male’, CAST(67.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Mauritania’, N’2000′, N’Male’, CAST(51.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Mauritius’, N’2000′, N’Male’, CAST(61.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Mexico’, N’2000′, N’Male’, CAST(64.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Micronesia (Federated States of)’, N’2000′, N’Male’, CAST(59.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Mongolia’, N’2000′, N’Male’, CAST(54.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Montenegro’, N’2000′, N’Male’, CAST(62.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Morocco’, N’2000′, N’Male’, CAST(59.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Mozambique’, N’2000′, N’Male’, CAST(41.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Myanmar’, N’2000′, N’Male’, CAST(53.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Namibia’, N’2000′, N’Male’, CAST(49.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Nepal’, N’2000′, N’Male’, CAST(54.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Netherlands’, N’2000′, N’Male’, CAST(67.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’New Zealand’, N’2000′, N’Male’, CAST(67.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Nicaragua’, N’2000′, N’Male’, CAST(48.60 AS Numeric(18, 2)))
GO
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Niger’, N’2000′, N’Male’, CAST(43.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Nigeria’, N’2000′, N’Male’, CAST(40.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Norway’, N’2000′, N’Male’, CAST(67.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Oman’, N’2000′, N’Male’, CAST(62.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Pakistan’, N’2000′, N’Male’, CAST(54.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Panama’, N’2000′, N’Male’, CAST(64.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Papua New Guinea’, N’2000′, N’Male’, CAST(51.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Paraguay’, N’2000′, N’Male’, CAST(61.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Peru’, N’2000′, N’Male’, CAST(57.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Philippines’, N’2000′, N’Male’, CAST(56.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Poland’, N’2000′, N’Male’, CAST(62.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Portugal’, N’2000′, N’Male’, CAST(65.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Qatar’, N’2000′, N’Male’, CAST(64.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Republic of Korea’, N’2000′, N’Male’, CAST(65.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Republic of Moldova’, N’2000′, N’Male’, CAST(57.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Romania’, N’2000′, N’Male’, CAST(60.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Russian Federation’, N’2000′, N’Male’, CAST(53.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Rwanda’, N’2000′, N’Male’, CAST(35.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Saint Lucia’, N’2000′, N’Male’, CAST(62.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Saint Vincent and the Grenadines’, N’2000′, N’Male’, CAST(61.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Samoa’, N’2000′, N’Male’, CAST(61.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Sao Tome and Principe’, N’2000′, N’Male’, CAST(53.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Saudi Arabia’, N’2000′, N’Male’, CAST(61.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Senegal’, N’2000′, N’Male’, CAST(49.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Serbia’, N’2000′, N’Male’, CAST(62.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Seychelles’, N’2000′, N’Male’, CAST(61.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Sierra Leone’, N’2000′, N’Male’, CAST(33.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Singapore’, N’2000′, N’Male’, CAST(68.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Slovakia’, N’2000′, N’Male’, CAST(61.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Slovenia’, N’2000′, N’Male’, CAST(63.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Solomon Islands’, N’2000′, N’Male’, CAST(58.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Somalia’, N’2000′, N’Male’, CAST(42.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’South Africa’, N’2000′, N’Male’, CAST(48.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’South Sudan’, N’2000′, N’Male’, CAST(41.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Spain’, N’2000′, N’Male’, CAST(66.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Sri Lanka’, N’2000′, N’Male’, CAST(61.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Sudan’, N’2000′, N’Male’, CAST(49.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Suriname’, N’2000′, N’Male’, CAST(57.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Swaziland’, N’2000′, N’Male’, CAST(41.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Sweden’, N’2000′, N’Male’, CAST(68.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Switzerland’, N’2000′, N’Male’, CAST(67.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Syrian Arab Republic’, N’2000′, N’Male’, CAST(60.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Tajikistan’, N’2000′, N’Male’, CAST(53.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Thailand’, N’2000′, N’Male’, CAST(61.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Macedonia’, N’2000′, N’Male’, CAST(62.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Timor-Leste’, N’2000′, N’Male’, CAST(50.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Togo’, N’2000′, N’Male’, CAST(47.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Tonga’, N’2000′, N’Male’, CAST(63.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Trinidad and Tobago’, N’2000′, N’Male’, CAST(59.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Tunisia’, N’2000′, N’Male’, CAST(62.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Turkey’, N’2000′, N’Male’, CAST(59.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Turkmenistan’, N’2000′, N’Male’, CAST(54.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Uganda’, N’2000′, N’Male’, CAST(39.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Ukraine’, N’2000′, N’Male’, CAST(56.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’United Arab Emirates’, N’2000′, N’Male’, CAST(64.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’United Kingdom’, N’2000′, N’Male’, CAST(67.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’United Republic of Tanzania’, N’2000′, N’Male’, CAST(42.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’United States of America’, N’2000′, N’Male’, CAST(65.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Uruguay’, N’2000′, N’Male’, CAST(63.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Uzbekistan’, N’2000′, N’Male’, CAST(57.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Vanuatu’, N’2000′, N’Male’, CAST(60.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Venezuela’, N’2000′, N’Male’, CAST(60.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Viet Nam’, N’2000′, N’Male’, CAST(59.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Yemen’, N’2000′, N’Male’, CAST(52.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Zambia’, N’2000′, N’Male’, CAST(36.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Zimbabwe’, N’2000′, N’Male’, CAST(39.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Afghanistan’, N’2015′, N’Female’, CAST(53.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Albania’, N’2015′, N’Female’, CAST(71.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Algeria’, N’2015′, N’Female’, CAST(67.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Angola’, N’2015′, N’Female’, CAST(47.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Antigua and Barbuda’, N’2015′, N’Female’, CAST(68.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Argentina’, N’2015′, N’Female’, CAST(70.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Armenia’, N’2015′, N’Female’, CAST(68.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Australia’, N’2015′, N’Female’, CAST(72.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Austria’, N’2015′, N’Female’, CAST(73.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Azerbaijan’, N’2015′, N’Female’, CAST(66.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Bahamas’, N’2015′, N’Female’, CAST(68.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Bahrain’, N’2015′, N’Female’, CAST(67.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Bangladesh’, N’2015′, N’Female’, CAST(62.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Barbados’, N’2015′, N’Female’, CAST(68.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Belarus’, N’2015′, N’Female’, CAST(69.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Belgium’, N’2015′, N’Female’, CAST(72.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Belize’, N’2015′, N’Female’, CAST(63.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Benin’, N’2015′, N’Female’, CAST(52.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Bhutan’, N’2015′, N’Female’, CAST(61.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Bolivia (Plurinational State of)’, N’2015′, N’Female’, CAST(64.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Bosnia and Herzegovina’, N’2015′, N’Female’, CAST(70.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Botswana’, N’2015′, N’Female’, CAST(58.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Brazil’, N’2015′, N’Female’, CAST(67.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Brunei Darussalam’, N’2015′, N’Female’, CAST(71.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Bulgaria’, N’2015′, N’Female’, CAST(69.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Burkina Faso’, N’2015′, N’Female’, CAST(52.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Burundi’, N’2015′, N’Female’, CAST(53.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Cote d”Ivoire’, N’2015′, N’Female’, CAST(47.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Cabo Verde’, N’2015′, N’Female’, CAST(65.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Cambodia’, N’2015′, N’Female’, CAST(60.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Cameroon’, N’2015′, N’Female’, CAST(51.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Canada’, N’2015′, N’Female’, CAST(73.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Central African Republic’, N’2015′, N’Female’, CAST(47.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Chad’, N’2015′, N’Female’, CAST(47.10 AS Numeric(18, 2)))
GO
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Chile’, N’2015′, N’Female’, CAST(72.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’China’, N’2015′, N’Female’, CAST(69.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Colombia’, N’2015′, N’Female’, CAST(67.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Comoros’, N’2015′, N’Female’, CAST(57.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Congo’, N’2015′, N’Female’, CAST(57.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Costa Rica’, N’2015′, N’Female’, CAST(71.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Croatia’, N’2015′, N’Female’, CAST(71.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Cuba’, N’2015′, N’Female’, CAST(70.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Cyprus’, N’2015′, N’Female’, CAST(72.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Czech Republic’, N’2015′, N’Female’, CAST(71.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Democratic People”s Republic of Korea’, N’2015′, N’Female’, CAST(66.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Democratic Republic of the Congo’, N’2015′, N’Female’, CAST(53.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Denmark’, N’2015′, N’Female’, CAST(72.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Djibouti’, N’2015′, N’Female’, CAST(57.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Dominican Republic’, N’2015′, N’Female’, CAST(67.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Ecuador’, N’2015′, N’Female’, CAST(68.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Egypt’, N’2015′, N’Female’, CAST(63.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’El Salvador’, N’2015′, N’Female’, CAST(67.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Equatorial Guinea’, N’2015′, N’Female’, CAST(52.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Eritrea’, N’2015′, N’Female’, CAST(57.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Estonia’, N’2015′, N’Female’, CAST(72.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Ethiopia’, N’2015′, N’Female’, CAST(57.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Fiji’, N’2015′, N’Female’, CAST(65.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Finland’, N’2015′, N’Female’, CAST(72.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’France’, N’2015′, N’Female’, CAST(74.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Gabon’, N’2015′, N’Female’, CAST(58.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Gambia’, N’2015′, N’Female’, CAST(54.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Georgia’, N’2015′, N’Female’, CAST(69.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Germany’, N’2015′, N’Female’, CAST(72.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Ghana’, N’2015′, N’Female’, CAST(56.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Greece’, N’2015′, N’Female’, CAST(73.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Grenada’, N’2015′, N’Female’, CAST(66.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Guatemala’, N’2015′, N’Female’, CAST(64.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Guinea’, N’2015′, N’Female’, CAST(51.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Guinea-Bissau’, N’2015′, N’Female’, CAST(52.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Guyana’, N’2015′, N’Female’, CAST(60.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Haiti’, N’2015′, N’Female’, CAST(56.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Honduras’, N’2015′, N’Female’, CAST(66.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Hungary’, N’2015′, N’Female’, CAST(69.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Iceland’, N’2015′, N’Female’, CAST(73.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’India’, N’2015′, N’Female’, CAST(60.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Indonesia’, N’2015′, N’Female’, CAST(63.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Iran (Islamic Republic of)’, N’2015′, N’Female’, CAST(66.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Iraq’, N’2015′, N’Female’, CAST(62.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Ireland’, N’2015′, N’Female’, CAST(72.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Israel’, N’2015′, N’Female’, CAST(73.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Italy’, N’2015′, N’Female’, CAST(73.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Jamaica’, N’2015′, N’Female’, CAST(68.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Japan’, N’2015′, N’Female’, CAST(77.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Jordan’, N’2015′, N’Female’, CAST(65.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Kazakhstan’, N’2015′, N’Female’, CAST(66.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Kenya’, N’2015′, N’Female’, CAST(57.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Kiribati’, N’2015′, N’Female’, CAST(60.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Kuwait’, N’2015′, N’Female’, CAST(66.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Kyrgyzstan’, N’2015′, N’Female’, CAST(66.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Lao People”s Democratic Republic’, N’2015′, N’Female’, CAST(59.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Latvia’, N’2015′, N’Female’, CAST(70.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Lebanon’, N’2015′, N’Female’, CAST(66.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Lesotho’, N’2015′, N’Female’, CAST(47.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Liberia’, N’2015′, N’Female’, CAST(53.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Libya’, N’2015′, N’Female’, CAST(65.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Lithuania’, N’2015′, N’Female’, CAST(70.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Luxembourg’, N’2015′, N’Female’, CAST(73.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Madagascar’, N’2015′, N’Female’, CAST(58.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Malawi’, N’2015′, N’Female’, CAST(52.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Malaysia’, N’2015′, N’Female’, CAST(68.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Maldives’, N’2015′, N’Female’, CAST(70.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Mali’, N’2015′, N’Female’, CAST(50.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Malta’, N’2015′, N’Female’, CAST(72.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Mauritania’, N’2015′, N’Female’, CAST(55.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Mauritius’, N’2015′, N’Female’, CAST(69.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Mexico’, N’2015′, N’Female’, CAST(69.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Micronesia (Federated States of)’, N’2015′, N’Female’, CAST(63.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Mongolia’, N’2015′, N’Female’, CAST(65.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Montenegro’, N’2015′, N’Female’, CAST(69.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Morocco’, N’2015′, N’Female’, CAST(65.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Mozambique’, N’2015′, N’Female’, CAST(50.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Myanmar’, N’2015′, N’Female’, CAST(60.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Namibia’, N’2015′, N’Female’, CAST(59.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Nepal’, N’2015′, N’Female’, CAST(62.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Netherlands’, N’2015′, N’Female’, CAST(73.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’New Zealand’, N’2015′, N’Female’, CAST(72.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Nicaragua’, N’2015′, N’Female’, CAST(67.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Niger’, N’2015′, N’Female’, CAST(54.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Nigeria’, N’2015′, N’Female’, CAST(48.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Norway’, N’2015′, N’Female’, CAST(73.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Oman’, N’2015′, N’Female’, CAST(67.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Pakistan’, N’2015′, N’Female’, CAST(58.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Panama’, N’2015′, N’Female’, CAST(70.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Papua New Guinea’, N’2015′, N’Female’, CAST(58.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Paraguay’, N’2015′, N’Female’, CAST(66.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Peru’, N’2015′, N’Female’, CAST(67.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Philippines’, N’2015′, N’Female’, CAST(63.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Poland’, N’2015′, N’Female’, CAST(71.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Portugal’, N’2015′, N’Female’, CAST(73.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Qatar’, N’2015′, N’Female’, CAST(68.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Republic of Korea’, N’2015′, N’Female’, CAST(75.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Republic of Moldova’, N’2015′, N’Female’, CAST(67.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Romania’, N’2015′, N’Female’, CAST(69.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Russian Federation’, N’2015′, N’Female’, CAST(67.80 AS Numeric(18, 2)))
GO
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Rwanda’, N’2015′, N’Female’, CAST(60.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Saint Lucia’, N’2015′, N’Female’, CAST(67.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Saint Vincent and the Grenadines’, N’2015′, N’Female’, CAST(65.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Samoa’, N’2015′, N’Female’, CAST(69.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Sao Tome and Principe’, N’2015′, N’Female’, CAST(60.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Saudi Arabia’, N’2015′, N’Female’, CAST(64.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Senegal’, N’2015′, N’Female’, CAST(59.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Serbia’, N’2015′, N’Female’, CAST(69.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Seychelles’, N’2015′, N’Female’, CAST(69.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Sierra Leone’, N’2015′, N’Female’, CAST(44.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Singapore’, N’2015′, N’Female’, CAST(75.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Slovakia’, N’2015′, N’Female’, CAST(70.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Slovenia’, N’2015′, N’Female’, CAST(73.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Solomon Islands’, N’2015′, N’Female’, CAST(62.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Somalia’, N’2015′, N’Female’, CAST(48.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’South Africa’, N’2015′, N’Female’, CAST(56.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’South Sudan’, N’2015′, N’Female’, CAST(50.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Spain’, N’2015′, N’Female’, CAST(74.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Sri Lanka’, N’2015′, N’Female’, CAST(69.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Sudan’, N’2015′, N’Female’, CAST(56.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Suriname’, N’2015′, N’Female’, CAST(64.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Swaziland’, N’2015′, N’Female’, CAST(52.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Sweden’, N’2015′, N’Female’, CAST(73.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Switzerland’, N’2015′, N’Female’, CAST(74.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Syrian Arab Republic’, N’2015′, N’Female’, CAST(59.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Tajikistan’, N’2015′, N’Female’, CAST(65.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Thailand’, N’2015′, N’Female’, CAST(68.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Macedonia’, N’2015′, N’Female’, CAST(69.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Timor-Leste’, N’2015′, N’Female’, CAST(62.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Togo’, N’2015′, N’Female’, CAST(53.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Tonga’, N’2015′, N’Female’, CAST(67.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Trinidad and Tobago’, N’2015′, N’Female’, CAST(65.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Tunisia’, N’2015′, N’Female’, CAST(68.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Turkey’, N’2015′, N’Female’, CAST(67.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Turkmenistan’, N’2015′, N’Female’, CAST(63.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Uganda’, N’2015′, N’Female’, CAST(55.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Ukraine’, N’2015′, N’Female’, CAST(67.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’United Arab Emirates’, N’2015′, N’Female’, CAST(68.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’United Kingdom ‘, N’2015′, N’Female’, CAST(72.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’United Republic of Tanzania’, N’2015′, N’Female’, CAST(55.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’United States of America’, N’2015′, N’Female’, CAST(70.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Uruguay’, N’2015′, N’Female’, CAST(70.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Uzbekistan’, N’2015′, N’Female’, CAST(65.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Vanuatu’, N’2015′, N’Female’, CAST(66.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Venezuela’, N’2015′, N’Female’, CAST(68.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Viet Nam’, N’2015′, N’Female’, CAST(69.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Yemen’, N’2015′, N’Female’, CAST(58.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Zambia’, N’2015′, N’Female’, CAST(55.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Zimbabwe’, N’2015′, N’Female’, CAST(53.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Afghanistan’, N’2000′, N’Female’, CAST(48.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Albania’, N’2000′, N’Female’, CAST(66.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Algeria’, N’2000′, N’Female’, CAST(63.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Angola’, N’2000′, N’Female’, CAST(40.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Antigua and Barbuda’, N’2000′, N’Female’, CAST(66.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Argentina’, N’2000′, N’Female’, CAST(67.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Armenia’, N’2000′, N’Female’, CAST(66.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Australia’, N’2000′, N’Female’, CAST(71.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Austria’, N’2000′, N’Female’, CAST(70.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Azerbaijan’, N’2000′, N’Female’, CAST(61.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Bahamas’, N’2000′, N’Female’, CAST(65.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Bahrain’, N’2000′, N’Female’, CAST(65.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Bangladesh’, N’2000′, N’Female’, CAST(56.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Barbados’, N’2000′, N’Female’, CAST(66.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Belarus’, N’2000′, N’Female’, CAST(65.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Belgium’, N’2000′, N’Female’, CAST(70.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Belize’, N’2000′, N’Female’, CAST(62.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Benin’, N’2000′, N’Female’, CAST(48.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Bhutan’, N’2000′, N’Female’, CAST(52.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Bolivia (Plurinational State of)’, N’2000′, N’Female’, CAST(56.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Bosnia and Herzegovina’, N’2000′, N’Female’, CAST(67.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Botswana’, N’2000′, N’Female’, CAST(41.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Brazil’, N’2000′, N’Female’, CAST(64.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Brunei Darussalam’, N’2000′, N’Female’, CAST(68.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Bulgaria’, N’2000′, N’Female’, CAST(66.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Burkina Faso’, N’2000′, N’Female’, CAST(44.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Burundi’, N’2000′, N’Female’, CAST(45.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Cote d”Ivoire’, N’2000′, N’Female’, CAST(42.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Cabo Verde’, N’2000′, N’Female’, CAST(61.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Cambodia’, N’2000′, N’Female’, CAST(48.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Cameroon’, N’2000′, N’Female’, CAST(45.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Canada’, N’2000′, N’Female’, CAST(71.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Central African Republic’, N’2000′, N’Female’, CAST(40.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Chad’, N’2000′, N’Female’, CAST(42.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Chile’, N’2000′, N’Female’, CAST(69.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’China’, N’2000′, N’Female’, CAST(65.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Colombia’, N’2000′, N’Female’, CAST(65.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Comoros’, N’2000′, N’Female’, CAST(53.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Congo’, N’2000′, N’Female’, CAST(46.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Costa Rica’, N’2000′, N’Female’, CAST(69.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Croatia’, N’2000′, N’Female’, CAST(69.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Cuba’, N’2000′, N’Female’, CAST(68.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Cyprus’, N’2000′, N’Female’, CAST(70.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Czech Republic’, N’2000′, N’Female’, CAST(68.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Democratic People”s Republic of Korea’, N’2000′, N’Female’, CAST(61.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Democratic Republic of the Congo’, N’2000′, N’Female’, CAST(45.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Denmark’, N’2000′, N’Female’, CAST(69.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Djibouti’, N’2000′, N’Female’, CAST(51.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Dominican Republic’, N’2000′, N’Female’, CAST(64.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Ecuador’, N’2000′, N’Female’, CAST(65.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Egypt’, N’2000′, N’Female’, CAST(61.10 AS Numeric(18, 2)))
GO
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’El Salvador’, N’2000′, N’Female’, CAST(63.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Equatorial Guinea’, N’2000′, N’Female’, CAST(47.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Eritrea’, N’2000′, N’Female’, CAST(44.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Estonia’, N’2000′, N’Female’, CAST(67.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Ethiopia’, N’2000′, N’Female’, CAST(46.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Fiji’, N’2000′, N’Female’, CAST(62.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Finland’, N’2000′, N’Female’, CAST(70.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’France’, N’2000′, N’Female’, CAST(72.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Gabon’, N’2000′, N’Female’, CAST(52.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Gambia’, N’2000′, N’Female’, CAST(49.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Georgia’, N’2000′, N’Female’, CAST(66.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Germany’, N’2000′, N’Female’, CAST(70.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Ghana’, N’2000′, N’Female’, CAST(51.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Greece’, N’2000′, N’Female’, CAST(71.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Grenada’, N’2000′, N’Female’, CAST(63.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Guatemala’, N’2000′, N’Female’, CAST(60.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Guinea’, N’2000′, N’Female’, CAST(46.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Guinea-Bissau’, N’2000′, N’Female’, CAST(46.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Guyana’, N’2000′, N’Female’, CAST(59.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Haiti’, N’2000′, N’Female’, CAST(52.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Honduras’, N’2000′, N’Female’, CAST(62.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Hungary’, N’2000′, N’Female’, CAST(66.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Iceland’, N’2000′, N’Female’, CAST(71.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’India’, N’2000′, N’Female’, CAST(54.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Indonesia’, N’2000′, N’Female’, CAST(60.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Iran (Islamic Republic of)’, N’2000′, N’Female’, CAST(62.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Iraq’, N’2000′, N’Female’, CAST(62.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Ireland’, N’2000′, N’Female’, CAST(69.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Israel’, N’2000′, N’Female’, CAST(70.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Italy’, N’2000′, N’Female’, CAST(71.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Jamaica’, N’2000′, N’Female’, CAST(65.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Japan’, N’2000′, N’Female’, CAST(75.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Jordan’, N’2000′, N’Female’, CAST(63.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Kazakhstan’, N’2000′, N’Female’, CAST(62.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Kenya’, N’2000′, N’Female’, CAST(46.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Kiribati’, N’2000′, N’Female’, CAST(58.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Kuwait’, N’2000′, N’Female’, CAST(65.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Kyrgyzstan’, N’2000′, N’Female’, CAST(63.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Lao People”s Democratic Republic’, N’2000′, N’Female’, CAST(52.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Latvia’, N’2000′, N’Female’, CAST(67.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Lebanon’, N’2000′, N’Female’, CAST(62.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Lesotho’, N’2000′, N’Female’, CAST(43.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Liberia’, N’2000′, N’Female’, CAST(44.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Libya’, N’2000′, N’Female’, CAST(63.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Lithuania’, N’2000′, N’Female’, CAST(68.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Luxembourg’, N’2000′, N’Female’, CAST(70.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Madagascar’, N’2000′, N’Female’, CAST(51.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Malawi’, N’2000′, N’Female’, CAST(37.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Malaysia’, N’2000′, N’Female’, CAST(66.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Maldives’, N’2000′, N’Female’, CAST(62.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Mali’, N’2000′, N’Female’, CAST(43.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Malta’, N’2000′, N’Female’, CAST(69.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Mauritania’, N’2000′, N’Female’, CAST(52.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Mauritius’, N’2000′, N’Female’, CAST(66.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Mexico’, N’2000′, N’Female’, CAST(67.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Micronesia (Federated States of)’, N’2000′, N’Female’, CAST(60.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Mongolia’, N’2000′, N’Female’, CAST(59.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Montenegro’, N’2000′, N’Female’, CAST(66.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Morocco’, N’2000′, N’Female’, CAST(61.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Mozambique’, N’2000′, N’Female’, CAST(43.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Myanmar’, N’2000′, N’Female’, CAST(56.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Namibia’, N’2000′, N’Female’, CAST(50.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Nepal’, N’2000′, N’Female’, CAST(55.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Netherlands’, N’2000′, N’Female’, CAST(70.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’New Zealand’, N’2000′, N’Female’, CAST(70.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Nicaragua’, N’2000′, N’Female’, CAST(60.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Niger’, N’2000′, N’Female’, CAST(43.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Nigeria’, N’2000′, N’Female’, CAST(41.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Norway’, N’2000′, N’Female’, CAST(71.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Oman’, N’2000′, N’Female’, CAST(64.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Pakistan’, N’2000′, N’Female’, CAST(54.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Panama’, N’2000′, N’Female’, CAST(68.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Papua New Guinea’, N’2000′, N’Female’, CAST(54.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Paraguay’, N’2000′, N’Female’, CAST(63.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Peru’, N’2000′, N’Female’, CAST(62.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Philippines’, N’2000′, N’Female’, CAST(61.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Poland’, N’2000′, N’Female’, CAST(68.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Portugal’, N’2000′, N’Female’, CAST(70.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Qatar’, N’2000′, N’Female’, CAST(66.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Republic of Korea’, N’2000′, N’Female’, CAST(70.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Republic of Moldova’, N’2000′, N’Female’, CAST(63.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Romania’, N’2000′, N’Female’, CAST(66.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Russian Federation’, N’2000′, N’Female’, CAST(63.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Rwanda’, N’2000′, N’Female’, CAST(44.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Saint Lucia’, N’2000′, N’Female’, CAST(64.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Saint Vincent and the Grenadines’, N’2000′, N’Female’, CAST(63.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Samoa’, N’2000′, N’Female’, CAST(66.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Sao Tome and Principe’, N’2000′, N’Female’, CAST(56.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Saudi Arabia’, N’2000′, N’Female’, CAST(64.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Senegal’, N’2000′, N’Female’, CAST(51.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Serbia’, N’2000′, N’Female’, CAST(66.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Seychelles’, N’2000′, N’Female’, CAST(68.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Sierra Leone’, N’2000′, N’Female’, CAST(34.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Singapore’, N’2000′, N’Female’, CAST(71.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Slovakia’, N’2000′, N’Female’, CAST(68.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Slovenia’, N’2000′, N’Female’, CAST(69.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Solomon Islands’, N’2000′, N’Female’, CAST(59.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Somalia’, N’2000′, N’Female’, CAST(44.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’South Africa’, N’2000′, N’Female’, CAST(52.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’South Sudan’, N’2000′, N’Female’, CAST(43.20 AS Numeric(18, 2)))
GO
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Spain’, N’2000′, N’Female’, CAST(71.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Sri Lanka’, N’2000′, N’Female’, CAST(66.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Sudan’, N’2000′, N’Female’, CAST(52.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Suriname’, N’2000′, N’Female’, CAST(61.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Swaziland’, N’2000′, N’Female’, CAST(42.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Sweden’, N’2000′, N’Female’, CAST(71.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Switzerland’, N’2000′, N’Female’, CAST(71.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Syrian Arab Republic’, N’2000′, N’Female’, CAST(63.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Tajikistan’, N’2000′, N’Female’, CAST(59.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Thailand’, N’2000′, N’Female’, CAST(65.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Macedonia’, N’2000′, N’Female’, CAST(66.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Timor-Leste’, N’2000′, N’Female’, CAST(53.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Togo’, N’2000′, N’Female’, CAST(48.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Tonga’, N’2000′, N’Female’, CAST(65.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Trinidad and Tobago’, N’2000′, N’Female’, CAST(64.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Tunisia’, N’2000′, N’Female’, CAST(66.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Turkey’, N’2000′, N’Female’, CAST(63.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Turkmenistan’, N’2000′, N’Female’, CAST(60.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Uganda’, N’2000′, N’Female’, CAST(40.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Ukraine’, N’2000′, N’Female’, CAST(65.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’United Arab Emirates’, N’2000′, N’Female’, CAST(66.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’United Kingdom’, N’2000′, N’Female’, CAST(70.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’United Republic of Tanzania’, N’2000′, N’Female’, CAST(43.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’United States of America’, N’2000′, N’Female’, CAST(68.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Uruguay’, N’2000′, N’Female’, CAST(68.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Uzbekistan’, N’2000′, N’Female’, CAST(62.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Vanuatu’, N’2000′, N’Female’, CAST(63.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Venezuela’, N’2000′, N’Female’, CAST(67.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Viet Nam’, N’2000′, N’Female’, CAST(65.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Yemen’, N’2000′, N’Female’, CAST(53.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Zambia’, N’2000′, N’Female’, CAST(39.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Zimbabwe’, N’2000′, N’Female’, CAST(39.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Afghanistan’, N’2015′, N’Male’, CAST(51.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Albania’, N’2015′, N’Male’, CAST(66.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Algeria’, N’2015′, N’Male’, CAST(65.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Angola’, N’2015′, N’Male’, CAST(44.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Antigua and Barbuda’, N’2015′, N’Male’, CAST(66.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Argentina’, N’2015′, N’Male’, CAST(65.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Armenia’, N’2015′, N’Male’, CAST(64.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Australia’, N’2015′, N’Male’, CAST(70.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Austria’, N’2015′, N’Male’, CAST(70.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Azerbaijan’, N’2015′, N’Male’, CAST(62.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Bahamas’, N’2015′, N’Male’, CAST(64.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Bahrain’, N’2015′, N’Male’, CAST(66.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Bangladesh’, N’2015′, N’Male’, CAST(61.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Barbados’, N’2015′, N’Male’, CAST(65.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Belarus’, N’2015′, N’Male’, CAST(60.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Belgium’, N’2015′, N’Male’, CAST(69.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Belize’, N’2015′, N’Male’, CAST(60.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Benin’, N’2015′, N’Male’, CAST(52.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Bhutan’, N’2015′, N’Male’, CAST(61.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Bolivia (Plurinational State of)’, N’2015′, N’Male’, CAST(61.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Bosnia and Herzegovina’, N’2015′, N’Male’, CAST(66.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Botswana’, N’2015′, N’Male’, CAST(55.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Brazil’, N’2015′, N’Male’, CAST(63.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Brunei Darussalam’, N’2015′, N’Male’, CAST(69.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Bulgaria’, N’2015′, N’Male’, CAST(63.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Burkina Faso’, N’2015′, N’Male’, CAST(52.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Burundi’, N’2015′, N’Male’, CAST(50.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Cote d”Ivoire’, N’2015′, N’Male’, CAST(46.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Cabo Verde’, N’2015′, N’Male’, CAST(63.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Cambodia’, N’2015′, N’Male’, CAST(55.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Cameroon’, N’2015′, N’Male’, CAST(49.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Canada’, N’2015′, N’Male’, CAST(71.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Central African Republic’, N’2015′, N’Male’, CAST(44.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Chad’, N’2015′, N’Male’, CAST(45.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Chile’, N’2015′, N’Male’, CAST(68.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’China’, N’2015′, N’Male’, CAST(67.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Colombia’, N’2015′, N’Male’, CAST(62.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Comoros’, N’2015′, N’Male’, CAST(54.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Congo’, N’2015′, N’Male’, CAST(55.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Costa Rica’, N’2015′, N’Male’, CAST(68.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Croatia’, N’2015′, N’Male’, CAST(67.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Cuba’, N’2015′, N’Male’, CAST(68.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Cyprus’, N’2015′, N’Male’, CAST(70.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Czech Republic’, N’2015′, N’Male’, CAST(67.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Democratic People”s Republic of Korea’, N’2015′, N’Male’, CAST(61.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Democratic Republic of the Congo’, N’2015′, N’Male’, CAST(50.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Denmark’, N’2015′, N’Male’, CAST(70.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Djibouti’, N’2015′, N’Male’, CAST(54.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Dominican Republic’, N’2015′, N’Male’, CAST(63.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Ecuador’, N’2015′, N’Male’, CAST(65.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Egypt’, N’2015′, N’Male’, CAST(61.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’El Salvador’, N’2015′, N’Male’, CAST(60.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Equatorial Guinea’, N’2015′, N’Male’, CAST(50.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Eritrea’, N’2015′, N’Male’, CAST(54.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Estonia’, N’2015′, N’Male’, CAST(65.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Ethiopia’, N’2015′, N’Male’, CAST(54.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Fiji’, N’2015′, N’Male’, CAST(60.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Finland’, N’2015′, N’Male’, CAST(69.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’France’, N’2015′, N’Male’, CAST(70.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Gabon’, N’2015′, N’Male’, CAST(56.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Gambia’, N’2015′, N’Male’, CAST(53.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Georgia’, N’2015′, N’Male’, CAST(63.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Germany’, N’2015′, N’Male’, CAST(69.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Ghana’, N’2015′, N’Male’, CAST(54.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Greece’, N’2015′, N’Male’, CAST(70.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Grenada’, N’2015′, N’Male’, CAST(63.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Guatemala’, N’2015′, N’Male’, CAST(59.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Guinea’, N’2015′, N’Male’, CAST(51.50 AS Numeric(18, 2)))
GO
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Guinea-Bissau’, N’2015′, N’Male’, CAST(50.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Guyana’, N’2015′, N’Male’, CAST(57.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Haiti’, N’2015′, N’Male’, CAST(54.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Honduras’, N’2015′, N’Male’, CAST(63.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Hungary’, N’2015′, N’Male’, CAST(64.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Iceland’, N’2015′, N’Male’, CAST(71.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’India’, N’2015′, N’Male’, CAST(58.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Indonesia’, N’2015′, N’Male’, CAST(60.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Iran (Islamic Republic of)’, N’2015′, N’Male’, CAST(66.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Iraq’, N’2015′, N’Male’, CAST(58.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Ireland’, N’2015′, N’Male’, CAST(70.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Israel’, N’2015′, N’Male’, CAST(71.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Italy’, N’2015′, N’Male’, CAST(71.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Jamaica’, N’2015′, N’Male’, CAST(65.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Japan’, N’2015′, N’Male’, CAST(72.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Jordan’, N’2015′, N’Male’, CAST(64.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Kazakhstan’, N’2015′, N’Male’, CAST(59.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Kenya’, N’2015′, N’Male’, CAST(53.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Kiribati’, N’2015′, N’Male’, CAST(56.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Kuwait’, N’2015′, N’Male’, CAST(65.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Kyrgyzstan’, N’2015′, N’Male’, CAST(61.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Lao People”s Democratic Republic’, N’2015′, N’Male’, CAST(56.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Latvia’, N’2015′, N’Male’, CAST(63.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Lebanon’, N’2015′, N’Male’, CAST(64.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Lesotho’, N’2015′, N’Male’, CAST(45.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Liberia’, N’2015′, N’Male’, CAST(51.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Libya’, N’2015′, N’Male’, CAST(62.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Lithuania’, N’2015′, N’Male’, CAST(62.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Luxembourg’, N’2015′, N’Male’, CAST(70.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Madagascar’, N’2015′, N’Male’, CAST(55.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Malawi’, N’2015′, N’Male’, CAST(50.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Malaysia’, N’2015′, N’Male’, CAST(64.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Maldives’, N’2015′, N’Male’, CAST(68.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Mali’, N’2015′, N’Male’, CAST(51.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Malta’, N’2015′, N’Male’, CAST(70.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Mauritania’, N’2015′, N’Male’, CAST(54.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Mauritius’, N’2015′, N’Male’, CAST(64.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Mexico’, N’2015′, N’Male’, CAST(65.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Micronesia (Federated States of)’, N’2015′, N’Male’, CAST(61.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Mongolia’, N’2015′, N’Male’, CAST(58.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Montenegro’, N’2015′, N’Male’, CAST(66.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Morocco’, N’2015′, N’Male’, CAST(64.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Mozambique’, N’2015′, N’Male’, CAST(48.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Myanmar’, N’2015′, N’Male’, CAST(57.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Namibia’, N’2015′, N’Male’, CAST(55.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Nepal’, N’2015′, N’Male’, CAST(60.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Netherlands’, N’2015′, N’Male’, CAST(71.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’New Zealand’, N’2015′, N’Male’, CAST(70.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Nicaragua’, N’2015′, N’Male’, CAST(60.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Niger’, N’2015′, N’Male’, CAST(53.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Nigeria’, N’2015′, N’Male’, CAST(46.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Norway’, N’2015′, N’Male’, CAST(70.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Oman’, N’2015′, N’Male’, CAST(65.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Pakistan’, N’2015′, N’Male’, CAST(57.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Panama’, N’2015′, N’Male’, CAST(66.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Papua New Guinea’, N’2015′, N’Male’, CAST(54.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Paraguay’, N’2015′, N’Male’, CAST(64.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Peru’, N’2015′, N’Male’, CAST(63.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Philippines’, N’2015′, N’Male’, CAST(58.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Poland’, N’2015′, N’Male’, CAST(65.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Portugal’, N’2015′, N’Male’, CAST(69.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Qatar’, N’2015′, N’Male’, CAST(67.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Republic of Korea’, N’2015′, N’Male’, CAST(70.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Republic of Moldova’, N’2015′, N’Male’, CAST(61.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Romania’, N’2015′, N’Male’, CAST(64.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Russian Federation’, N’2015′, N’Male’, CAST(59.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Rwanda’, N’2015′, N’Male’, CAST(52.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Saint Lucia’, N’2015′, N’Male’, CAST(64.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Saint Vincent and the Grenadines’, N’2015′, N’Male’, CAST(63.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Samoa’, N’2015′, N’Male’, CAST(64.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Sao Tome and Principe’, N’2015′, N’Male’, CAST(57.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Saudi Arabia’, N’2015′, N’Male’, CAST(64.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Senegal’, N’2015′, N’Male’, CAST(57.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Serbia’, N’2015′, N’Male’, CAST(65.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Seychelles’, N’2015′, N’Male’, CAST(62.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Sierra Leone’, N’2015′, N’Male’, CAST(43.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Singapore’, N’2015′, N’Male’, CAST(71.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Slovakia’, N’2015′, N’Male’, CAST(65.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Slovenia’, N’2015′, N’Male’, CAST(68.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Solomon Islands’, N’2015′, N’Male’, CAST(61.50 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Somalia’, N’2015′, N’Male’, CAST(46.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’South Africa’, N’2015′, N’Male’, CAST(51.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’South Sudan’, N’2015′, N’Male’, CAST(49.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Spain’, N’2015′, N’Male’, CAST(70.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Sri Lanka’, N’2015′, N’Male’, CAST(64.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Sudan’, N’2015′, N’Male’, CAST(54.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Suriname’, N’2015′, N’Male’, CAST(61.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Swaziland’, N’2015′, N’Male’, CAST(49.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Sweden’, N’2015′, N’Male’, CAST(71.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Switzerland’, N’2015′, N’Male’, CAST(71.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Syrian Arab Republic’, N’2015′, N’Male’, CAST(52.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Tajikistan’, N’2015′, N’Male’, CAST(59.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Thailand’, N’2015′, N’Male’, CAST(64.80 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Macedonia’, N’2015′, N’Male’, CAST(65.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Timor-Leste’, N’2015′, N’Male’, CAST(59.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Togo’, N’2015′, N’Male’, CAST(52.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Tonga’, N’2015′, N’Male’, CAST(64.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Trinidad and Tobago’, N’2015′, N’Male’, CAST(61.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Tunisia’, N’2015′, N’Male’, CAST(65.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Turkey’, N’2015′, N’Male’, CAST(64.50 AS Numeric(18, 2)))
GO
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Turkmenistan’, N’2015′, N’Male’, CAST(56.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Uganda’, N’2015′, N’Male’, CAST(53.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Ukraine’, N’2015′, N’Male’, CAST(60.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’United Arab Emirates’, N’2015′, N’Male’, CAST(68.00 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’United Kingdom’, N’2015′, N’Male’, CAST(70.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’United Republic of Tanzania’, N’2015′, N’Male’, CAST(52.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’United States of America’, N’2015′, N’Male’, CAST(67.70 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Uruguay’, N’2015′, N’Male’, CAST(65.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Uzbekistan’, N’2015′, N’Male’, CAST(59.90 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Vanuatu’, N’2015′, N’Male’, CAST(63.40 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Venezuela’, N’2015′, N’Male’, CAST(62.30 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Viet Nam’, N’2015′, N’Male’, CAST(63.20 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Yemen’, N’2015′, N’Male’, CAST(57.10 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Zambia’, N’2015′, N’Male’, CAST(51.60 AS Numeric(18, 2)))
INSERT [dbo].[WHO_LifeExpectancy] ([Country], [Year], [Gender], [Age]) VALUES (N’Zimbabwe’, N’2015′, N’Male’, CAST(50.90 AS Numeric(18, 2)))

Descriptive Statistics with SQL and R – 1

I started my re-discovery of statistics with an introduction here. This second post is about descriptive statistics – very basic, simple statistics you begin with as a learner. Descriptive Statistics are also called Summary Statistics and serve to describe/summarize the data. They allow you to understand what the data is about and get a feel for its common features. There are two types of descriptive statistics

Measures of Central Tendency – for example, mean, median and mode.
Measures of Dispersion – or variation from Central Tendency such as standard deviation, interquartile range and so on.

You can figure out minimum and maximum values, outliers, average and most frequently occuring values with descriptive statistics. It takes you no further than that – it is not for deeper diagnostics of data, predictive or prescriptive analytics – but it is where you begin with in terms of understanding your data. In this post I took 5 very basic measures of descriptive statistics in category 1 for my specific measure – which is life expectancy across the globe.

Minimum life expectancy
Maximum life expectancy
Mean or Average life expectancy
Median or Central/mid point value of life expectancy
Mode or most common life expectancy.

It is easy to understand what are minimum and maximum values.They help you understand how wide the data set is. Some people also look at number of nulls in the dataset.
Mean or average is the sum of all values divided by number of values. Mean is very commonly used but does a poor job when there are outliers in the data such an unsually large or small value that can skew the average value.
Median is what you see as mid-point on a sorted scale of values. In other words median is the physical center of the data.Since median is not mathematically based it is rarely used in calculations. It does help with outliers better than mean does.
Mode is the most common value – very useful when you need to know to understand what are the values that occur most frequently. Mode can be used on nominal and ordinal data, hence it is the most commonly used measure of central tendency. There can be more than one mode in a sample.

The formulas to derive at these values are relatively simple – I tried them using both T-SQL and R, and also calling the R script via SQL. T-SQL is not really the best tool for statistical analysis, although it is useful for a beginner to get started.R are on the other hand has built-in functions for most of this.

With R integration into SQL Server 2016 we can pull an R script and integrate it rather easily. I will be covering all 3 approaches. I am using a small dataset – a single table with 915 rows, with a SQL Server 2016 installation and R Studio. The complexities of doing this type of analysis in the real world with bigger datasets involve setting various options for performance and dealing with memory issues – because R is very memory intensive and single threaded.

My table and the data it contains can be created with scripts here. For this specific post I used just one column in the table – age. For further posts I will be using the other fields such as country and gender.

Using T-SQL:

Below are my T-SQL Queries to get minimum, maximum, mean and mode. The mode is rather difficult using T-SQL. Given how easy it is do with R, I did not spend a lot of time on it. How to arrive at the mode of a dataset using T-SQL has been researched well and information can be found here for those interested.

SELECT MIN(age) AS [MINIMUM-AGE],MAX(age) AS [MAXIMUM-AGE],
ROUND((SUM(age)/COUNT(*)),2) AS MEANAGE FROM [dbo].[WHO_LifeExpectancy]
WHERE AGE IS NOT NULL

SELECT TOP 1 AGE AS MODE FROM [dbo].[WHO_LifeExpectancy]
GROUP BY AGE
ORDER BY count(*) DESC

The results I got were as below:
sql-results

Using R:

I downloaded and installed R Studio from here. The script should work just the same with any other version of R.
Before running the actual functions to get results, one has to load up the right libraries in R and connect to the database, then load the table contents into what is called a dataframe in R.Below commands help us do that.

install.packages(“RODBC”)
library(RODBC)

cn <- odbcDriverConnect(connection=”Driver={SQL Server Native Client 11.0};server=MALATH-PC\\SQL;database=WorldHealth;Uid=sa;Pwd=<password>”)

data <- sqlQuery(cn, ‘select age from [dbo].[WHO_LifeExpectancy] where age is not null’)

The data in my table is now in a dataframe called ‘data’ with R. To run statistical functions I need to ‘unpivot’ the dataframe into a single vector, and I have to use the ‘unlist‘ function in R for that purpose. When I run the R script via SQL, this is not necessary as it reads directly from the SQL tables. The R script i used to get the values is as below.

# Calculate the minimum value of data
minvalue<- min(unlist(data))
cat(“Minimum life expectancy”, minvalue)

#Calculate the maximum value of data
maxvalue<-max(unlist(data))
cat(“Maximum life expectancy”, maxvalue)

# Find mean.
data.mean <-mean(unlist(data))
cat(“Average Life Expectancy”, data.mean)

#Find mode
# Create the function.
getmode <- function(v) {
uniqv <- unique(v)
uniqv[which.max(tabulate(match(v, uniqv)))]
}

# Calculate the mode using the user function.
data.mode <- getmode(unlist(data))
cat(“Most common life expectancy”, data.mode)

data.median<-median(unlist(data))
data.median

Note that aside from mode all the rest are built-in functions in R. I borrowed the code for mode from here (the cool thing about R is the huge # of pre written scripts to do just about anything).

The results I got are as below:

r-studio

To be noted that the values of max, min, mean and mode are exactly the same as what we got from T-SQL which means this is correct.

3. Using R function calls with T-SQL

Details on configuration needed to use R within SQL Server are explained here.

The last and final step was to try the same script, without certain R specific commans such as ‘unlist’ to unlist the dataframe, and ‘cat’ to display concatenated results. The scripts are as below. The first one is the call to basic statistics and the second is to get the mode. I separated the function for mode into a script in itself as it was multiple lines and hard to include within same call.

EXEC sp_execute_external_script
@language = N’R’
,@script = N’minvalue <-min(InputDataSet$LifeExpectancies);
cat(“Minimum life expectancy”, minvalue,”\n”);
maxvalue <-max(InputDataSet$LifeExpectancies);
cat(” Maximum life expectancy”, maxvalue,”\n”);
average <-mean(InputDataSet$LifeExpectancies);
cat(” Average life expectancy”, average,”\n”);
medianle <-median(InputDataSet$LifeExpectancies);
cat(” Median Life Expectancy”, medianle,”\n”);
‘
,@input_data_1 = N’SELECT LifeExpectancies = Age FROM [WorldHealth].[dbo].[WHO_LifeExpectancy];’
;

EXEC sp_execute_external_script
@language = N’R’
,@script = N’getmode <- function(v) {
uniqv <- unique(v)
uniqv[which.max(tabulate(match(v, uniqv)))]
};
modele <- getmode(InputDataSet$LifeExpectancies);
cat(” Most Common Life Expectancy”, modele);
‘
,@input_data_1 = N’SELECT LifeExpectancies = Age FROM [WorldHealth].[dbo].[WHO_LifeExpectancy];’
;

sql-r-results

Other than a slight variation in mode , which i suspect is because of decimal rounding issues, the results are exactly the same as what we got via TSQL and R Studio.

In the next post I am going to deal with measure of dispersion. Thank you for reading and do leave me comments if you can!

Basic Statistics with SQL – Introduction

I was a student of statistics in school and college. I didn’t get to use much of anything I learned at school, and this was considered one of them. But apparently with the boom in interest in data mining, knowledge of statistics has become more important than ever before. Along with learning basics of statistics comes numerous tools available to mine data, and get appropriate metrics for business. For many people including me – we’d like to get involved with meaningful data mining but don’t know where to start. I personally decided to go back into revising some concepts I knew back in the days off the top of my head. I am going to blog every week on one concept that I am re-learning and applying to some data. I have great interest in data related to healthcare, so I used a data set available for public download from World Health Organization to help me. I also used T-SQL to run basic statistical queries. T-SQL is far from the best tool there is for statistical analysis, but it is certainly useful for getting a start on the subject of understanding and summarizing data.

You are given a dataset. It could a table, or multiple tables. What are the appropriate questions to ask before you get around to analyzing/mining this dataset? Below are a few that are recommended that I found useful to begin with:

What is the variable being measured? (There may be multiple, but for simplicity’s sake, let us make it 1).
In my case that is life expectancy of people around the globe,summarized at country level.
What is the population used? (The population is the potential collection of people that are ideally part of the sample used.)
People living in the countries around the globe.
What is the sample used? (The sample is the subset of the population used for this specific purpose)
People living in the countries targeted for this study.

The reason for asking these questions is to ensure that the dataset is representative of what we intend to present – if we say we are presenting statistics on global life expectancy there better be numbers related to that from many different countries around the world. There need not be every country on the list, but several countries are necessary to make the sample worthy of study. Sampling and sample size is in itself a very vast and deep subject. But this is just about understanding its basics and why we ask certain questions.

The last question that would determine the nature of our queries is about type of the variable being measured. Data used for statistical analysis can fall into one of 4 categories ,also called statistical scales – Nominal, Ordinal, Interval and Ratio. Like it is with rules of normalization – there are 4 rules to determine nature of measurement –

Identity – each value is unique
Magnitude – values have a relationship to each other
Equal Intervals – difference between two unique values is the same
Minimum value of 0 – the minimal value of the variable is 0.

Applying these rules to the above types of data –

Nominal data is what falls into specific mutually exclusive categories (the ones commonly under radio buttons) – male/female, ethnicity, nationality and so on. It satisfies rule 1.

Ordinal data is basically nominal data but has buckets that are gradeable or have some sort of order to them – such as ‘how good was this presentation – excellent to horrible’, or ‘how do you feel’, or even for example, work related titles – like data entry clerk, programmer, dba, senior dba and so on. It satisfies rules 1 and 2.

Interval data is numbers, and like ordinal – very specific numbers but you can calculate the difference between them. Interval data satisfies rules 1,2 and 3 but not 4 – because it does not stop at 0. An example would be temperature.

Ratio data is numbers like interval data but the minimum stops at 0. This enables data to be ratio friendly and hence is the best kind for statistical analysis.Examples would be weight, speed of a vehicle and so on.

In my specific data set – the variable am analyzing is life expectancies/age, which is ratio data by some and ordinal by others. This link addresses why. (There are a lot of such ambiguities and in the end what we call it is secondary to the value we derive out it). Now that i know my data, i need to go about running some basic statistics on it. More on that in the next post.

TSQL Tuesday #75 – PowerBI

SqlTuesday

This month’s TSQL Tuesday post is from one of my favorite people in the community – Jorge Segarra a.k.a. SQL Chicken. It is an invite to play with a new and shiny toy – Power BI. Now – like most people, my initial reaction was like ‘naaah, am not a BI person!’. I dread TSQL Tuesdays that leave me staring at a wall wondering what to write, and there have been a few of them. Certain features are not easy to try in a test lab environment – and work environments do not always lend themselves to that flexibility. But this seemed like something very easy to install and play with, on one’s own desktop.

After some hiccups with email and such which Jorge helped me resolve – (details on how to download the tool are in his post) I got the tool installed very easily. I considered various test data to play with it – felt it would be fun to use data accumulated over our sql saturdays at Louisville, which I have been the lead organizer for. We have had 8 events to date, but only 5 are available as history on website. But this was information enough. I pulled the reports on attendee registration going back five years from the sql saturday website, saved them as excel files, removed attendee personal information, and consolidated all of it into one CSV file. I learned later that you can actually do some data scrubbing within PowerBI itself but this was something I did outside and was ready with.

I launched the PowerBI desktop – pointed to my csv file as data source, and bingo, I was ready to go. The reports I needed were not raw data from the file – needed some grouping and consolidation – so I clicked on new query – which by default will bring up your raw data for you. In my case I needed the data to be grouped in several ways for my reports.Details of grouping are as below.

pb5

I created 4 queries – one each for each of my reports.
1 Query 1 – really simple, year wise grouping of attendee count.
2 Query 2 – two levels of grouping – year, meal preferences, count of people with those preferences.
3 Query 3 – two levels of grouping- year, opt in choice for emails, count for opt in choices.
4 Query 4 – two levels of grouping – year, state attendee is from, count of attendees. Here I had to filter out some junk data for name of state – and consolidate some verbage, like KY=Kentucky and so on.

When I was done the list of my data sources looked like below.

pb6

Now with my data ready, I launched into getting my reports up. I used each data source from above list for each graph (you can also use multiple but wanted to keep this simple).

pb4

The interactive graph can be viewed with better fonts here

https://app.powerbi.com/view?r=eyJrIjoiY2EzMWI1ZWQtYTQxNC00YjJhLTgxZTQtYjEyZjBkNzU5YTllIiwidCI6IjU2MzQ0OTU1LTJiZWYtNGFhZi1iYzg2LTQ4YWEzNzMzNzI0MSIsImMiOjZ9

Based on above graphs I was able to draw following conclusions:

1 First bar graph on the top left: Attendee by year: Our highest turnout was in 2011 (301) in the past five years. Hope to beat that record in 2016! Last year was 263 people.

2 Second horizontal bar on the right: Food payment preferences by year: A lot more people opted to bring their own lunch last year – this may be because we hiked the lunch fee to 10$ after several years (yeah Kentucky:)) . There are more people being comped as well due to higher number of sponsors and volunteers, which is not a bad thing. It would be interesting to see how this graph changes this year, because we provided a fantastic BBQ lunch last year. We have also hiked lunch fee from 10-12$ so it could go either way.

3 First bar graph on bottom left: Optin attendees over years: People who have opted out from vendor emails has gone up and was highest last year.We need to work harder on getting more people to opt-in as this means lesser reach for vendors.

4 Last graph bottom right: Attendee count by state: Looks like we did not have significant people from TN until 2013…(I filtered out #s less than 10 for this graph as we are not interested in 1 or 2 random attendees from other states). Our largest # of people are from KY, which is no surprise at all..but what was surprising to me for sure was that IN and OH both had around similar number of people.We did have several speakers from OH – but not 23, and there are certainly more people coming in from there. This shows that we have to promote our event harder in OH, as well as work on getting more people from TN, another border state.

All said and done, I had an absolute ball doing this. Not only is it easy and convenient to use but comes in handy for a variety of different things, including analysing personal finances and such. I highly recommend it!