To prepare for this paper:
• Using the SPSS software, open the Afrobarometer dataset.
• Construct a research question that can be answered with a multiple regression analysis.
• Once you perform your multiple regression analysis, review Chapter 11 of the Wagner text to understand how to copy and paste your output into your Word document.
For this Part 1 paper:
Write a 2-page analysis of your multiple regression results for each research question. In your analysis, display the data for the output. Based on your results, provide an explanation of what the implications of social change might be.
Required Readings
Wagner, III, W. E. (2020). Using IBM® SPSS® statistics for research methods and social science statistics (7th ed.). Thousand Oaks, CA: Sage Publications.
• Chapter 2, “Transforming Variables”
• Chapter 11, “Editing Output” (previously read in Week 2, 3, 4, 5. 6, 7, 8, and 9)
Allison, P. D. (1999). Multiple regression: A primer. Thousand Oaks, CA: Pine Forge Press/Sage Publications.
Multiple Regression: A Primer, by Allison, P. D. Copyright 1998 by Sage College. Reprinted by permission of Sage College via the Copyright Clearance Center.
• Chapter 6, “What are the Assumptions of Multiple Regression?” (pp. 119–136)
Allison, P. D. (1999). Multiple regression: A primer. Thousand Oaks, CA: Pine Forge Press/Sage Publications.
Multiple Regression: A Primer, by Allison, P. D. Copyright 1998 by Sage College. Reprinted by permission of Sage College via the Copyright Clearance Center.
• Chapter 7, “What can be done about Multicollinearity?” (pp. 137–152)
Multiple Regression: A Primer, by Allison, P. D. Copyright 1998 by Sage College. Reprinted by permission of Sage College via the Copyright Clearance Center.
Warner, R. M. (2012). Applied statistics from bivariate through multivariate techniques (2nd ed.). Thousand Oaks, CA: Sage Publications.
Applied Statistics From Bivariate Through Multivariate Techniques, 2nd Edition by Warner, R.M. Copyright 2012 by Sage College. Reprinted by permission of Sage College via the Copyright Clearance Center.
• Chapter 12, “Dummy Predictor Variables in Multiple Regression”
Applied Statistics From Bivariate Through Multivariate Techniques, 2nd Edition by Warner, R.M. Copyright 2012 by Sage College. Reprinted by permission of Sage College via the Copyright Clearance Center.
Non-Normally Distributed Errors. (1991). In J. Fox (Ed.), Regression Diagnostics. (pp. 41-49). Thousand Oaks, CA: SAGE Publications, Inc.
Fox, J. (1991). Regression diagnostics. Thousand Oaks, CA: SAGE Publications.
Discrete Data. (1991). In J. Fox (Ed.), Regression Diagnostics. (pp. 62-67). Thousand Oaks, CA: SAGE Publications, Inc.
Nonconstant Error Variance. (1991). In J. Fox (Ed.), Regression Diagnostics. (pp. 49-54). Thousand Oaks, CA: SAGE Publications, Inc.
Nonlinearity. (1991). In J. Fox (Ed.), Regression Diagnostics. (pp. 54-62). Thousand Oaks, CA: SAGE Publications, Inc.
Outlying and Influential Data. (1991). In J. Fox (Ed.), Regression Diagnostics. (pp. 22-41). Thousand Oaks, CA: SAGE Publications, Inc.
Fox, J. (Ed.). (1991). Regression diagnostics. Thousand Oaks, CA: SAGE Publications.
• Chapter 3, “Outlying and Influential Data” (pp. 22–41)
• Chapter 4, “Non-Normally Distributed Errors” (pp. 41–49)
• Chapter 5, “Nonconstant Error Variance” (pp. 49–54)
• Chapter 6, “Nonlinearity” (pp. 54–62)
• Chapter 7, “Discrete Data” (pp. 62–67)
Note: You will access these chapters through the Walden Library databases.
Document: Walden University: Research Design Alignment
Use proper APA format, citations, and referencing for your analysis, research question, and display of output.
