# 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.

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##### 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.

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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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