Question

Please note that for all problems in this course, the standard cut-off (alpha) for a test of significance will be .05, and you always report the exact power unless SPSS output states p=.000 (you’d report p<.001). Also, remember that we divide the p value in half when reporting one-tailed tests with 1 – 2 groups.

Problem Set 1: Two-way ANOVA (8 pts) Research Scenario An Industrial/Organizational psychologist conducted a study examining differences in sex (women and men) and primary mode of communication with superiors (face, email, indirect) on perceived likelihood of receiving a raise in the next 6 months. Perceived likelihood was measured in percent likelihood of expecting a raise (e.g., 0 indicates they absolutely do not expect a raise in the next 6 months). Twenty-eight participants completed the study. Their results are in the table below. Conduct a two-way ANOVA to determine whether perceived likelihood of receiving a raise in the next 6 months is affected by sex and/or primary mode of communication. Remember to name and define your variables (your two independent variables and your one dependent variable) under the “Variable View,” then return to the “Data View” to enter and analyze the data. (Note the data set is small to ease your burden – use a two-way ANOVA regardless!) Face Email Indirect Men 85 100 90 95 100 99 90 100 80 85 90 95 40 30 Women 50 75 80 70 25 10 5 50 75 75 5 10 25 10

9. Paste the relevant SPSS output, including post hocs if necessary. (2 pts)

10. Create the most appropriate graph(s) for this data given the results. (2 pts)

11. Write an APA-style Results section based on your analysis. All homework “Results sections” should follow the examples provided in the presentations and textbooks. They should include the statistical statement within a complete sentence that mentions the type of test conducted, whether the test was significant, and if relevant, effect size and/or post hoc analyses. Don’t forget to include a decision about the null hypothesis. (4 pts)

Answer 1

The above analysis performed in R. You can use any tool to do the same but the imp thing is to be able to interpret the results which I have explained above.

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