The Correlation Between Household With Very Low Work Intensity, Employment Rate and Tertiary Educational Attainment

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The regression analysis is a statistical instrument used for finding out the relationship between variables. The types of regression models are Simple and Multiple. The simple one defines between two variables which one is the dependent one and the other is the regressor. The Multiple model is the one comparing many regressors to one dependent variable.
In this project we are concentrating on finding out if there is a correlation between the Household with very low work intensity of 14 countries with the employment rate and tertiary educational attainment for the same ones using the simple and multiple regression model.
The information was collected from Eurostat website ( with the containing sample of 14 European countries from east to west: Romania, Hungary, Austria, Croatia, Bulgaria, Lithuania, Greece, Belgium, France, Germany, Spain, Luxembourg, Netherlands and Finland. The study was based in the year of 2012.
The dependent variable is Household with very low work intensity(y) with the independent variables Employment rate(x1) and Tertiary Educational Attainment(x2).
The indicator persons living in households with low work intensity is defined as the number of persons living in a household having a work intensity below a threshold set at 0.20.
The work intensity of a household is the ratio of the total number of months that all working-age household members have worked during the income reference year and the total number of months the same household members theoretically could have worked in the same period. 
A working person is aged 18-59 years, with the exclusion of students in the age group between 18 and 24 years. Households composed only of children, of students aged less than 25 and/or people aged 60 or more are completely excluded from the indicator calculation.
Employment rate deals with the labor force of each country that has at least one job. It relates to the work intensity of a household because it shows a connection between the ones actually working and the ones not.
Tertiary Educational Attainment is the level of higher education of studies. It connects with both Employment and Household because it provides more proof on actual facts of persons having a job. This makes the theory of household members true on how many can be in a single period.
So in this analysis we can say that it helps identify the exact variable numbers that can be considered true by relating to other factors calculated in the process. The higher percentage rate in employment and age group on tertiary educational attainment in average numbers, the better is the work intensity in a household.
On the west side of Europe we got a sample of 7 countries selected and the average employment rate was found to be 71.31% with a standard deviation of 6.622. For the east side of Europe we got a sample of 7 other countries selected with an average employment rate of 63.31% and a standard deviation of 7.826. From the calculations obtained we observe how on the west side of Europe there is a higher claim of rating than of its eastern part. This is what we are interested in finding out.
The initial hypothesis is the employment rate for the West and East side countries should be equal.
The alternative hypothesis is the employment rate for West Countries are bigger than the East Countries.
H0: u1 = u2 => u1- u2= u2- u1=0
H1: u1> u2 => u1- u2 >0
We will perform the test to the right.
Cut off value: 1.645
RR: (1.645,?)
zcalc = (x1-x2)/?(s1/n1+s2/n2)
zcalc = (71.316-63.316)/?(6.62/7+7.82/7)= 5.56
Zcalc = 5.56 > 1.645 => we can conclude that it falls in the rejection region, so in 95% of the cases we can reject H0. It can be said that the employment rate is higher in the western side than in the east.
An economist also stated that the Tertiary Education Attainment age average is around 30 for the countries on both east and west side of Europe. A sample of 14 countries was selected that presumes by the facts that it's actually the age of 35.49 that considers with a very high education. The standard deviation is 9.82 for the problem. We want to find out exactly if the two parties computed are different.

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