Selig Chong
HDEV

The three sets of variables are tested based on a two sample test, a chi-square test, and ANOVA. For the two sample t-test I am testing the null hypothesis that men and women have the same number of family generations in household. Secondly, I am using a chi-square method to find the relationship political party and having a rifle at home. The third and final set of variables that I will test will be the ANOVA in which I will examine the relationship between religious preference and educational attainment.
Group Statistics

RESPONDENTS SEX
N
Mean
Std. Deviation
Std. Error Mean
NUMBER OF FAMILY GENERATIONS IN HOUSEHOLD
MALE
648
1.43
.698
.027

FEMALE
852
1.53
.704
.024

For the first set of variable, we are using a two sample t-test. According to the outcome data, 1.53-1.43=.10, we see that woman slightly have more number of family generations in household than males. Now I have to see which results is necessary to use. This depends on the result from the Levene’s test for Equity of Variance. Since the p-value under this test for equality of variance is .417, I can assume that the variance of the two sex groups are the same. If the p-value of Levene’s test is less than the alpha .05, I need to use the unequal variance outcome. Since the p-value under Sig. (2-tail) is .006, I reject the null hypothesis and conclude that there is a difference between the mean score of male and woman at 5% significant level. The measurement of association are nominal. The Pearson chi-square has value of 35.917 with a degree of freedom of 14. The significance of this chi-square is to be .001. The measurement of association are nominal variables. Eight cells (33.3%) have expected count less than 5. The minimum expected count is .54. The interpretation is that political party affiliation and having a rifle at home are related.

My third analysis I am using education as the independent variable at what religious preference. The research hypothesis proposes that at least one of the means is different in order to predict that a difference