Our papers are 100% unique and written following academic standards and provided requirements. Get perfect grades by consistently using our writing services. Place your order and get a quality paper today. Rely on us and be on schedule! With our help, you'll never have to worry about deadlines again. Take advantage of our current 20% discount by using the coupon code GET20
Order a Similar Paper Order a Different Paper
Week 9: Multiple Regression
Last week you explored the predictive nature of bivariate, simple linear regression. As you found out, and its name implies, bivariate regression only uses one predictor variable. As social scientists, we frequently have questions that require the use of multiple predictor variables. Moreover, we often want to include control variables (i.e., workforce experience, knowledge, education, etc.) in our model. Multiple regression allows the researcher to build on bivariate regression by including all of the important predictor and control variables in the same model. This, in turn, assists in reducing error and provides a better explanation of the complex social world.
In this week, you will examine multiple regression. In your examination, you will construct research questions, evaluate research design, and analyze results related to multiple regression.
- Construct research questions
- Evaluate research design through research questions
- Analyze multiple regression
- Analyze measures multiple regression
- Evaluate significance of multiple regression
- Analyze results for multiple regression testing
- Analyze assumptions of correlation and bivariate regression (assessed in Week 10)
- Analyze implications for social change (assessed in Week 10)
- Evaluate research related to correlation and bivariate regression
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, III, W. E. (2020). Using IBM® SPSS® statistics for research methods and social science statistics (7th ed.). Thousand Oaks, CA: Sage Publications.
- Chapter 11, “Editing Output” (previously read in Week 2, 3, 4, 5. 6, 7, and 8)
Walden University Library. (n.d.). Course Guide and Assignment Help for RSCH 8210. Retrieved from http://academicguides.waldenu.edu/rsch8210
For help with this week’s research, see this Course Guide and related weekly assignment resources.
Document: Walden University: Research Design Alignment Table
Document: Data Set 2014 General Social Survey (dataset file)
Use this dataset to complete this week’s Discussion.
Note: You will need the SPSS software to open this dataset.
Laureate Education (Producer). (2016g). Multiple regression [Video file]. Baltimore, MD: Author.
Note: The approximate length of this media piece is 7 minutes.
In this media program, Dr. Matt Jones demonstrates multiple regression using the SPSS software.
Skill Builder: Interpreting the Results from Regression Models
To access these Skill Builders, navigate back to your Blackboard Course Home page, and locate “Skill Builders” in the left navigation pane. From there, click on the relevant Skill Builder link for this week.
You are encouraged to click through these and all Skill Builders to gain additional practice with these concepts. Doing so will bolster your knowledge of the concepts you’re learning this week and throughout the course.
Assignment: Multiple Regression in Practice
For this Assignment, you will continue your practice as a critical consumer of research. You will critically evaluate a scholarly article related to multiple regression.
To prepare for this Assignment:
- Use the Course Guide and Assignment Help found in this week’s Learning Resources and search for a quantitative article that includes multiple regression testing. Also, you can use as guide the Research Design Alignment Table located in this week’s Learning Resources.
For this Assignment:
Write a 3- to 5-paragraphs critique of the article (2 to 3 pages). In your critique, include responses to the following:
- Why did the authors use multiple regression?
- Do you think it’s the most appropriate choice? Why or why not?
- Did the authors display the data?
- Do the results stand alone? Why or why not?
- Did the authors report effect size? If yes, is this meaningful?