RELATIONSHIP BETWEEN POPULATION AND IMMIGRANT POPULATIONAlba Morera and Javier Pérez

Population: the total number of persons inhabiting a country, city, or any district or area.

Immigration: the international movement of people into a destination country of which they are not natives or where they do not possess citizenship in order to settle or reside there, especially as permanent residents or naturalized citizens

First we collected data from fifteen countries and put it on a table.

COUNTRIES POPULATION IMMIGRANT POPULATIONRussia 146.683.000 13.048.064Germany 82.040.000 9.895.244UK 65.593.000 7.804.131France 64.629.000 7.439.086Italy 60.832.000 572.457Spain 46.397.000 6.466.605Ukraine 42.670.000 5.151.378The Netherlands 17.022.000 1.964.922Turkey 77.695.904 1.864.889Belgium 11.336.000 1.159.801Sweden 9.901.000 1.519.510Bielorussia 9.502.000 1.085.396Austria 8.736.000 1.333.807Switzerland 8.362.000 2.335.059

Then we processed the data

Covariance provides a measure of the strength of the correlation between two or more sets of random variates.

The correlation coefficient is the degree in which the change in a set of variables is related. This means that we are trying to find out if the two variables have a correlation at all, how strong the correlation is and if the correlation is positive or negative. To find the exact correlation between variables, you will need to use the correlation coefficient equation. When solved, the correlation coefficient equation will give you a number between -1 and 1. The closer the number is to positive one, the stronger the positive correlation. The closer the number is to negative one, the stronger the negative correlation. And the closer the number is to zero, the weaker the correlation. Zero means there is no correlation between the variables.

The relation between these two variables is strong and positive because the number is really close to 1 and greater than 0.

Population mean 46.528.493Immigrant population mean 4.402.882Population Variance 1,49147E+15Immigrant population variance 1,43643E+13Covariance 1,18076E+14Coefficient of correlation 0,806700203

Y= 0,02X + 3.472.312,14 X= 0,09Y + 46.132.233,62

Afterwards we found out both regression lines in which x is the population and y the immigrant population.

The regression line allows the estimation of an unknown value of the variable Y over the variable X, and viceversa.

We estimated the immigrant population for BulgaryPopulation: 7.132.000 y= 0,02x + 3.472.312,14y= 0,02x7.132.000 + 3.472.312,14y= 3.614.952,14

We came to the conclussion that the result is quite reliable because the coefficient of correlation is very close to 1.