Malik_BUSI820_Assignment5

Busi820 Assignment 4 7.1 Run crosstabs and interpret the results of chi-square and phi (or Cramer’s V), as discussed in Chapter 7 and in the interpretation of Output 7.1, for: (a) academic track and marital status and (b) age group and marital status. Figure 1. Case Processing Summary Cases Valid Missing Total N Percent N Percent N Percent marital status * hours of study per week 49 98.0% 1 2.0% 50 100.0% marital status * hours of study per week Crosstabulation Count hours of study per week 2 4 5 7 8 10 12 13 marital status single 1 1 1 1 2 2 5 married 0 0 0 0 0 6 2 divorced 0 0 0 0 2 0 1 Total 1 1 1 1 4 8 8 marital status * hours of study per week Crosstabulation Count hours of study per week 15 17 18 20 22 24 30 35 marital status single 2 1 2 1 0 0 0 married 1 1 1 1 2 1 1 divorced 0 0 1 4 0 0 2 Total 3 2 4 6 2 1 3 marital status * hours of study per week Crosstabulation Count hours of study per week Total 38 marital status single 0 20 married 1 18 divorced 0 11 Total 1 49 Chi-Square Tests Value df Asymptotic Significance (2-sided) Pearson Chi-Square 38.273 a 32 .206 7.1.a. The Pearson chi-square test is a widely used statistical method for comparing experimental frequencies with theoretical frequencies derived from a hypothesis (Tallarida and Tallarida, 1987). In the context of comparing marital status and hours spent studying per week, the Pearson chi-square value is 38.273 with 32 degrees of freedom, 3

Busi820 Assignment 4 7.2 Select two other appropriate variables; run and interpret the output as we did in Output 7.1. Figure 3. Case Processing Summary Cases Valid Missing Total N Percent N Percent N Percent age group * hours per week spent working 49 98.0% 1 2.0% 50 100.0% age group * hours per week spent working Crosstabulation Count hours per week spent working 0 5 7 10 12 15 20 21 age group less than 22 4 0 1 1 1 1 0 22-29 2 1 0 2 0 1 2 30 or more 0 0 0 0 0 0 2 Total 6 1 1 3 1 2 4 age group * hours per week spent working Crosstabulation Count hours per week spent working 23 26 28 29 30 34 35 36 age group less than 22 1 1 0 0 0 0 2 22-29 0 0 2 1 0 0 1 30 or more 0 0 0 0 2 1 1 Total 1 1 2 1 2 1 4 age group * hours per week spent working Crosstabulation Count hours per week spent working Tota 37 38 40 42 43 45 50 age group less than 22 1 1 2 0 0 0 0 22-29 1 1 3 0 0 1 0 30 or more 0 1 2 1 2 0 1 Total 2 3 7 1 2 1 1 Chi-Square Tests Value df Asymptotic Significance (2-sided) Pearson Chi-Square 47.561 a 44 .330 Likelihood Ratio 54.559 44 .132 Linear-by-Linear Association 8.494 1 .004 7.2.a. The Pearson Chi-Square test showed a moderate value of 47.561 with 44 degrees of freedom, yielding an asymptotic significance level of .330. Similarly, the Likelihood Ratio test produced a value of 54.559 and the Linear-by-Linear Association test exhibited a value of 8.494. Both the Pearson Chi-Square test and Likelihood ratio yielded p-values greater than 0.05, indicating that there is no significant association between age group and hours spent working according to these tests. However, the Linear-by-Linear Association test yielded a smaller p-value of .004, which suggests a potential linear trend 6

Busi820 Assignment 4 used when dealing with small sample sizes or expected cell counts less than 5, also yielded a non-significant p-value. These results suggest that the presence or absence of children does not have a meaningful influence on the likelihood of watching TV sitcoms. 9

Busi820 Assignment 4 though the overall relationship is not strong enough to reach conventional significance levels. As explained by Kenney (1970), “eta coefficient squared serves as a descriptive index which, fora given set of data, can be used to assess the extent to which the variance in the dependent variable is accounted for, or explained, through the manipulation of the independent variables” (Kennedy, 1970). 12