Discussion: Categorical Data Analysis
As with the previous week’s Discussion, this Discussion assists in solidifying your understanding of statistical testing by engaging in some data analysis. This week you will once again work with a real, secondary dataset to construct a research question, perform categorical data analysis that answers the question, and interpret the results.
Whether in a scholarly or practitioner setting, good research and data analysis should have the benefit of peer feedback. For this Discussion, you will post your response to the hypothesis test, along with the results. Be sure and remember that the goal is to obtain constructive feedback to improve the research and its interpretation, so please view this as an opportunity to learn from one another.
To prepare for this Discussion:
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Order Paper Now· Review Chapters 10 and 11 of the Frankfort-Nachmias & Leon-Guerrero course text and the media program found in this week’s Learning Resources related to bivariate categorical tests.
· Create a research question using the General Social Survey dataset that can be answered using categorical analysis.
By Day 3
Use SPSS to answer the research question. Post your response to the following:
1. What is your research question?
2. What is the null hypothesis for your question?
3. What research design would align with this question?
4. What dependent variable was used and how is it measured?
5. What independent variable is used and how is it measured?
6. If you found significance, what is the strength of the effect?
7. Explain your results for a lay audience and further explain what the answer is to your research question.
Be sure to support your Main Post and Response Post with reference to the week’s Learning Resources and other scholarly evidence in APA Style.
Frankfort-Nachmias, C., & Leon-Guerrero, A. (2018). Social statistics for a diverse society (8th ed.). Thousand Oaks, CA: Sage Publications.
· Chapter 9, “Bivariate Tables” (pp. 235-268)
· Chapter 11, “The Chi-Square Test and Measures of Association” (pp. 269-302)