Discussion: Multiple Regression This Discussion assists in solidifying your understanding of statistical testing by engaging in some data analysis. This week you will work with a real, secondary dataset to construct a research question, estimate a multiple regression model, 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: Review this week’s Learning Resources and media program related to multiple regression. Create a research question using the General Social Survey that can be answered by multiple regression. Use SPSS to answer the research question. Post your response to the following: What is your research question? What is the null hypothesis for your question? What research design would align with this question? What dependent variable was used and how is it measured? What independent variable is used and how is it measured? What other variables were added to the multiple regression models as controls? What is the justification for adding the variables? If you found significance, what is the strength of the effect? Explain your results for a lay audience, explain what the answer 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. Respond to at least one of your colleagues’ posts and comment on the following: Do you think the variables are appropriately used? Why or why not? Does the addition of the control variables make sense to you? Why or why not? Does the analysis answer the research question? Be sure and provide constructive and helpful comments for possible improvement. If there was a significant effect, comments on the strength and its meaningfulness. As a lay reader, were you able to understand the results and their implications? Why or why not? Required Readings Laureate Education (Producer). (2016g). Multiple regression [Video file]. Baltimore, MD: Author. Frankfort-Nachmias, C., & Leon-Guerrero, A. (2018). Social statistics for a diverse society (8th ed.). Thousand Oaks, CA: Sage Publications. Chapter 12, “Regression and Correlation” (pp. 325-371) (previously read in Week 8) Wagner, W. E. (2016). Using IBM® SPSS® statistics for research methods and social science statistics (6th ed.). Thousand Oaks, CA: Sage Publications. Chapter 11, “Editing Output” (previously read in Week 2, 3, 4, 5. 6, 7, and 8)

This week you will put together each of the sections related to your chosen target population into a final paper. Make sure transitions are used between each segment to unify them and that your paper follows the order below:Introduction of paper and chosen population to studyDevelopmental milestones of target population supported by researchCase studyTheoretical analysis of case studySummarizing conclusionReferences page in APA formatAs you are connecting each of the sections into one paper, review any feedback and suggestions you may have received from your instructor and make changes accordingly. Proofread to make sure the sections connect together smoothly.Your paper must have at least 3 scholarly references for research and include citations in APA format on a References page at the end. The final paper should be at least 4-5 pages long, not including your cover page or References page.Submit your completed assignment to the drop box below. Please check the Course Calendar for specific due dates.Save your assignment as a Microsoft Word document. (Mac users, please remember to append the ".docx" extension to the filename.) The name of the file should be your first initial and last name, followed by an underscore and the name of the assignment, and an underscore and the date. An example is shown below: