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# Regression Analysis

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Data from 60 cities has been collected to investigate how human mortality relates to different socioeconomic factors.

The variables are:
Mortality (age adjusted mortality)
Education (median education)
PopDensity (Population density)
%Non-white (Percentage of non-whites)
%WC (Percentage of white collar workers)
Population (Population)
Pop/House (Population/household)
Incomes (Median income)

Trying to figure out how the dependent variable mortality can be described on the socio-economic factors algebraically.

*Some of the data sets did not show normality (by Anderson-Darling test) and thus were log transformed, whereupon they passed the Anderson-Darling test for normality.

##### Solution Summary

Data from 60 cities has been collected to investigate how human mortality relates to different socioeconomic factors.

The variables are:
Mortality (age adjusted mortality)
Education (median education)
PopDensity (Population density)
%Non-white (Percentage of non-whites)
%WC (Percentage of white collar workers)
Population (Population)
Pop/House (Population/household)
Incomes (Median income)

Trying to figure out how the dependent variable mortality can be described on the socio-economic factors algebraically.

*Some of the data sets did not show normality (by Anderson-Darling test) and thus were log transformed, whereupon they passed the Anderson-Darling test for normality.

##### Solution Preview

I used the regression estimated by the Least Squares Method to evaluate the algebraic relationship between the dependent variable and the listed independent ...

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