First we had to compare the demographic variables (age, gender, etc) to the socioeconomic variables (education, employment, etc) to see if any relationship between the two existed. Our first hypothesis is that gender does affect a person’s current housing status. This is of interest to us for many reasons. After learning more about gender roles in society, it is observed that women are perceived to have a restricted financial capacity than a male, therefore, is more unlikely to afford such luxuries as a home or home mortgage. Also, the discrimination of women is a problem in society that still must be corrected. Many steps have been taken in order to end the discrimination of women in the workplace, like the Equal Pay Ac

% of Total 6.9% 5.0% 12.0% 23.9%

When talking about the Chi Squared test, we must pay attention to the significance level. If this significance level is less than 5% than we must reject the null hypothesis and accept the alternative hypothesis that there is a relationship between a people’s gender and their current housing situation. In this case, the observed significance value is .000 (less than 5%); therefore, we know that the alternative hypothesis is accepted and that there is indeed a relationship between the two variables. The relationships that are noticed in our charts are that women compared to men rent more than they expected. This could be true because the women may either be single or divorced and cannot afford anything more than a rent payment for housing. Another relationship noticed is that more men own a home with a mortgage than expected and that fewer women than expected own a home with a mortgage. Also, men own a home outright less than expected and women own homes outright more than expected. These results may be true due to our society’s expectations for men to be higher than those of women.

Expected Count 268.0 436.0 296.0 1000.0

% within Sex of the respondent 28.9% 20.9% 50.2% 100.0%

Some topics in this essay:
Chi Squared, Consumer Finances, Sample Test, Expected Count, Pay Act, TENURE Current, Upper Age, Linear-by-Linear Association, current housing, home mortgage, SEX TENURE, chi squared, average age, squared test, Test Value, chi squared test, test value, housing status, current housing status, age homeowners, housing situation, own home, average age homeowners, owns home mortgage, person’s current housing,