Multiple Regression Analysis

Multiple Regression Analysis

Multiple Regression Analysis 150 150 Peter

Multiple Regression Analysis

Part 1
To prepare for this Part 1 of your Assignment:

  •  Review this week 9 and 10 Learning Resources and media program related to multiple regression.
  • Using the SPSS software, open the High School Longitudinal Study dataset found in the Learning Resources for this week.
  • 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 Assignment:
Write a 1- to 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.
Use proper APA format, citations, and referencing for your analysis, research question, and display of output.

Part  2
To prepare for this Part 2 of your Assignment:

  • Review Warner’s Chapter 12 and Chapter 2 of the Wagner course text and the media program found in this week’s Learning Resources and consider the use of dummy variables.
  • Using the SPSS software, open the High School Longitudinal Study dataset found in this week’s Learning Resources.

Consider the following:

  • Create a research question with metric variables and one variable that requires dummy coding. Estimate the model and report results.
  • Note: You are expected to perform regression diagnostics and report that as well.
  • Once you perform your analysis, review Chapter 11 of the Wagner text to understand how to copy and paste your output into your Word document.

For this Part 2 Assignment:
Write a 2- to 3-page analysis of your multiple regression using dummy variables 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.
Use proper APA format, citations, and referencing for your analysis, research question, and display of output.

RESOURCES
Frankfort-Nachmias, C., Leon-Guerrero, A., & Davis, G. (2020). Social statistics for a diverse society (9th ed.). Thousand Oaks, CA: Sage Publications.
• Chapter 12, “Regression and Correlation” (pp. 401-457) (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 8, “Correlation and Regression Analysis”
• 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.

RESOURCES

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.