Statistics Multiple Regression Paper

Statistics Multiple Regression Paper

Statistics Multiple Regression Paper

 

Review this week 9 and 10 Learning Resources and media      program related to multiple regression.

  • Using the SPSS software, open the Afrobarometer dataset      or the High School Longitudinal Study dataset (whichever you choose) found      in the Learning Resources for this week. Statistics Multiple Regression Paper
  • Based on the dataset you chose, 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.

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 Afrobarometer dataset      or the High School Longitudinal Study dataset (whichever you choose) 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.

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.

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)

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.

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 Table

Required Media

Laureate Education (Producer). (2016m). Regression diagnostics and model evaluation [Video file]. Baltimore, MD: Author.

Note: The approximate length of this media piece is 7 minutes.

In this media program, Dr. Matt Jones demonstrates regression diagnostics and model evaluation using the SPSS software.

Accessible player  –Downloads– Download Video w/CC Download Audio Download Transcript

Laureate Education (Producer). (2016). Dummy variables [Video file]. Baltimore, MD: Author.

Note: This media program is approximately 12 minutes.

In this media program, Dr. Matt Jones demonstrates dummy variables using the SPSS software.

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