Question

In this SPSS assignment, you will expand your understanding of inferential statistics involving a chi-square analysis. 1. For each variable gender and topic, conduct a Chi Square analysis to test if there is an even distribution across each level of each variable. (Hint: For this test, use the Nonparametric Test under the Analyze tab.) a. Upload the SPSS output. b. What are the null and alternative hypotheses for each variable? c. Report the results in APA format of the test for each of these hypotheses. 2. Once this analysis has been completed, the researcher is interested in determining how the distribution appears across the two variables combined. Conduct a Chi Square goodness-of-fit test for cross tabulation of gender and topic area. (Hint: For this test, use the Descriptive => Crosstabs under the Analyze tab.) a. Upload the SPSS output b. What are the null and alternative hypotheses for this test? c. Report the results in APA format of the test for each of these hypotheses. 3. Based on your personal experiences and interests, briefly discuss two variables to be used in a chi-square analysis. Please note, I have already generated the SPSS output so I do not need any of that. I just need help with the responses. Gender (M = male, F = female) Self-esteem scores Productivity scores M 64 25 M 68 28 F 74 36 M 75 38 F 76 34 F 79 36 F 80 40 F 82 41 M 68 22 M 70 38 F 74 39 F 76 34 F 78 38 F 79 37 M 82 45 M 85 46 F 71 30 M 73 34 F 75 33 M 77 36 M 78 38 M 80 42 F 83 46 F 86 49 M 73 37 F 74 38 M 77 32 M 77 35 F 78 36 M 81 45 F 84 49 F 87 48 F 77 36 M 71 33 F 75 34 F 76 36 M 79 38 M 83 48 F 89 48 F 91 49

Answer 1

1. We will conduct three Chi-square tests for each variable to test their distributions at each level. The null hypothesis and alternate hypothesis for each will be:

Ho1: The variable Gender is evenly distributed at each level OR Gender follows the expected distribution

Ha1: The variable Gender is not evenly distributed at each level OR Gender does not follow the expected distribution

Ho2: The variable Self-esteem scores is evenly distributed at each level

Ha2: The variable Self-esteem scores is not evenly distributed at each level

Ho3: The variable productivity scores is evenly distributed at each level

Ha3: The variable productivity scores is not evenly distributed at each level

Results in APA Format:

A chi square test for goodness of fit was run for the gender variable. A significant statistic emerged with a chi-square value of 0.400 and p>0.05 meaning that the variable is evenly distributed at each level.

A chi square test for goodness of fit was run for the 'self-esteem scores' variable. A significant statistic emerged with a chi-square value of 9.350 and p>0.05 meaning that the variable is evenly distributed at each level.

A chi square test for goodness of fit was run for the 'productivity scores' variable. A significant statistic emerged with a chi-square value of 22.700 and p>0.05 meaning that the variable is evenly distributed at each level.

2. For two variables combined, the chi-square test is used to test independence of two variables.

Ho1: Gender and Self-esteem scores are independent of each other.

Ha1: Gender and Self-esteem scores are not independent of each other.

A chi square test of independence was run between gender and self-esteem scores. An insignificant statistic emerged with a chi-square value of 20.8 and p (0.409) >0.05 stating that the the two variables are independent of each other.

Ho2: Gender and Productivity scores are independent of each other.

Ha2: Gender and Productivity scores are not independent of each other.

A chi square test of independence was run between gender and productivity scores. An insignificant statistic emerged with a chi-square value of 19.461 and p (0.364) >0.05 stating that the the two variables are independent of each other.

Ho3: Productivityand Self-esteem scores are independent of each other.

Ha3: Productivity and Self-esteem scores are not independent of each other.

A chi square test of independence was run between productivity scores and self-esteem scores. An insignificant statistic emerged with a chi-square value of 379.44 and p (0.231) >0.05 stating that the the two variables are independent of each other.

3. In a chi-square analysis, the two variables should always be used which are nominal or ordinal and have a few levels. For example, chi-square could be used between Gender (Two levels: Male and Female) and Smoking (Levels: Yes and No). The chi-square test should not be used for continuous numeric variables.