SPSS Statistics: Non-Parametric Data Analysis

SPSS Statistics: Non-Parametric Data Analysis

Non-Parametric Data Analysis

Examine the relationship between education (degree) and perception of life (life). Can you reject the null hypothesis that education and perception of life are independent? Summarize your findings.

A two-way contingency table analysis was conducted to evaluate whether the highest degree one earns influences the extent to which an individual reports that their life is exciting, routine or dull. The two variables were the respondent's highest degree earned and their rating of life being exciting, routine or dull. Degree and perception of life were found to be significantly related, Pearson X2 (8, N = 927) = 39.428, p = .000. An analysis of the clustered bar chart shows that individuals with a high school diploma were proportionally more likely to report that life was either exciting or dull, as compared to individuals with all other degree types.

The variables husbft and wifeft tell you whether a husband and a wife are employed full time. Use the sign test to test whether husbands and wives are equally likely to be employed full time. Summarize the conclusion.

The sign test showed significantly different rates of full time employment between husbands and wives, z = -7.944, p = .000. Although 478 of the 710 couples were both employed full time, in 177 cases the husband was more likely to work full time than the wife. In only 55 couples was the wife likely to work full time while the husband did not.

3. Use a nonparametric test to see if there is a difference in hours worked for males and females (variable hrs1). Summarize the conclusion.

A Mann-Whitney U test was conducted to evaluate the hypothesis that men and women work the same number of hours. The results of the test indicate that men and women do not work the same number of hours, z = -10.244, p = .000. Men had an average rank of 852.94 hours, while women had an average rang of 632.24 hours, indicating that on average, women worked fewer hours than men, in this sample.

4. Using a nonparametric test to see whether current salaries (variable salnow) for clerical employees differ for the four gender/race groups (variable sex/race). Compare your results from those from a parametric analysis. Summarize the conclusion.

A Kruskal-Wallis test was conducted to evaluate whether current salaries for clerical employees are equal between four groups: white males, minority males, white females and minority females. The results of the test indicate that the groups are significantly different from one another, X2 (3, 474) = 175.068, p = .000. The rank output indicates that white males had the highest average salary, followed by minority males, white females and finally minority females.