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Consumer credit and its affecting variables

The null hypothesis of this test is that there is no relationship between gender and housing status. To perform this test we must run a crosstabulation between the two variables (SEX/TENURE). The rows of the crosstab will include the gender of the population, and the columns will include the current housing status. We must notify our program (SPSS) to run the Chi squared test, and to include Observed counts, Expected counts, and row and column percentages. This will allow us to have all the information necessary to prove our hypothesis.
             After running the tests, it appears that there is enough information to come to an informed decision about or hypothesis that women are more unlikely to own a home or home mortgage than a man. The tables below were used to test our hypothesis.
             Crosstabulation of SEX and TENURE.
             Current housing status Total.
             owns home mortgage free owns home with a mortgage rents .
             Sex of the respondent male Count 199 386 176 761.
             Expected Count 203.9 331.8 225.3 761.
             % within Sex of the respondent 26.1% 50.7% 23.1% 100.0%.
             % within Current housing status 74.3% 88.5% 59.5% 76.1%.
             % of Total 19.9% 38.6% 17.6% 76.1%.
             female Count 69 50 120 239.
             Expected Count 64.1 104.2 70.7 239.
             % within Sex of the respondent 28.9% 20.9% 50.2% 100.0%.
             % within Current housing status 25.7% 11.5% 40.5% 23.9%.
             % of Total 6.9% 5.0% 12.0% 23.9%.
             Total Count 268 436 296 1000.
             Expected Count 268.0 436.0 296.0 1000.
             Chi Squared Test Results.
             Value df Asymp. Sig. (2-sided).
             Pearson Chi-Square 82.618(a) 2 .000.
             Likelihood Ratio 83.842 2 .000.
             Linear-by-Linear Association 19.146 1 .000.
             N of Valid Cases 1000 .
             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 .


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