Two-Proportions Test: Gender and Employment Status, Assignments of Data Analysis & Statistical Methods

Download Two-Proportions Test: Gender and Employment Status and more Assignments Data Analysis & Statistical Methods in PDF only on Docsity! Test of Two Proportions H0: M = F vs. Ha: M  F or Ha: M > F or Ha: M < F 8.49 SRS of undergraduates: is there any difference in the proportion of male vs. female employed students? H0: M = F vs. Ha: M  F Men Women Employed 728 603 Unemployed 89 149 Total 817 752 It appears that there is a difference between men and women and whether they are employed or not. We can do a two-sample test of proportions or a 2 test: User Specified Null Hypothesis Pop. 1 Prop. - Pop. 2 Prop = 0 Choice of Alpha = 0.05 Sample Evidence Sample 1 Sample 2 Sample Prop. 0.891065 0.801862 Sample Size 817 752 0.848311 Calculations p combo z-score 4.909829 4.920783 p-value 9.13E-07 8.63E-07 Decision Reject Null CI Lower Bound 0.124812 CI Upper Bound 0.053594 CLT Approx OK? YES z2 = 4.9207832 = 2 = 24.214. Both p-values are 0, so we conclude that there is a difference between men and women and whether they are employed or not. WORK * GENDER Crosstabulation 728 603 1331 693.1 637.9 1331.0 89.1% 80.2% 84.8% 89 149 238 123.9 114.1 238.0 10.9% 19.8% 15.2% 817 752 1569 817.0 752.0 1569.0 100.0% 100.0% 100.0% Count Expected Count % within GENDER Count Expected Count % within GENDER Count Expected Count % within GENDER employed unemployed WORK Total men women GENDER Total WORK unemployedemployed C o u n t 800 600 400 200 0 GENDER men women Chi-Square Tests 24.214b 1 .000 23.526 1 .000 24.354 1 .000 .000 .000 1569 Pearson Chi-Square Continuity Correctiona Likelihood Ratio Fisher's Exact Test N of Valid Cases Value df Asymp. Sig. (2-sided) Exact Sig. (2-sided) Exact Sig. (1-sided) Computed only for a 2x2 tablea. 0 cells (.0%) have expected count less than 5. The minimum expected count is 114.07. b.