Walden University Statistics

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.
  • 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.

Walden University Statistics

This week you have explored three different approaches to t tests. By this point, you know that each test has assumptions about the data and type of research questions it can answer. For this Assignment, you will be provided with three scenarios. As you read the scenarios, be sure and think about aligning the appropriate t test with the question. Consider whether the data are independent samples and if two samples are being compared.

To prepare for this Assignment:

  • Review the Learning Resources and the media programs      related to t tests.
  • For additional support, review the Skill      Builder: Research Design and Statistical Design and the Skill      Builder: Hypothesis Testing for Independent Samples t-test, which you      can find by navigating back to your Blackboard Course Home Page. From      there, locate the Skill Builder link in the left navigation pane.
  • Also, review the t test scenarios      found in this week’s Learning Resources and consider the three different      approaches of t tests:
    • Independent sample t test
    • Paired sample t test
    • One sample t test
  • Based on each of the three research scenarios provided,      open the High School Longitudinal Study dataset or the Afrobarometer      dataset from this week’s Learning Resources using SPSS software, then      choose and run the appropriate t test.
  • Once you perform your t test analyses,      review Chapter 11 of the Wagner text to understand how to copy and paste      your output into your Word document.

For this Assignment:

Write a 2 to 3-paragraph analysis of your t test results for each research scenario and include the SPSS syntax and output.  If you are using the Afrobarometer Dataset, report the mean of Q1 (Age). If you are using the HS Long Survey Dataset, report the mean of X1SES. Do not forget to evaluate if the t test assumptions are met, justify the selection of type of t test, and report the effect size. Based on your results, provide an explanation of what the implications of social change might be.

Learning Resources

Required Readings

Frankfort-Nachmias, C., Leon-Guerrero, A., & Davis, G. (2020). Social statistics for a diverse society (9th ed.). Thousand Oaks, CA: Sage Publications.

  • Chapter 8, “Testing Hypothesis” (pp. 243-279)

Wagner, III, W. E. (2020). Using IBM® SPSS® statistics for research methods and social science statistics (7th ed.). Thousand Oaks, CA: Sage Publications.

  • Chapter 6, “Testing Hypotheses Using Means and Cross-Tabulation” (previously read in Week 5)
  • Chapter 11, “Editing Output” (previously read in Week 2, 3, and 4)

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.

Fox, J. (1991). Discrete data. In Regression diagnostics (pp. 62-66). SAGE Publications, Inc., https://www-doi-org.ezp.waldenulibrary.org/10.4135/9781412985604

Fox, J. (1991). Regression diagnostics. SAGE Publications, Inc. https://www-doi-org.ezp.waldenulibrary.org/10.4135/9781412985604

Fox, J. (1991). Non-normally distributed errors. In Regression diagnostics (pp. 41-48). SAGE Publications, Inc., https://www-doi-org.ezp.waldenulibrary.org/10.4135/9781412985604

Fox, J. (1991). Nonconstant error variance. In Regression diagnostics (pp. 49-53). SAGE Publications, Inc., https://www-doi-org.ezp.waldenulibrary.org/10.4135/9781412985604

Fox, J. (1991). Nonlinearity. In Regression diagnostics (pp. 54-61). SAGE Publications, Inc., https://www-doi-org.ezp.waldenulibrary.org/10.4135/9781412985604

Fox, J. (1991). Outlying and influential data. In Regression diagnostics (pp. 22-40). SAGE Publications, Inc., https://www-doi-org.ezp.waldenulibrary.org/10.4135/9781412985604

Document: Week 6 t test Scenarios (PDF)

Use these scenarios to complete this week’s Assignment.

Document: Walden University: Research Design Alignment Table

Datasets

Your instructor will post the datasets for the course in the Doc Sharing section and in an Announcement. Your instructor may also recommend using a different dataset from the ones provided here.

Required Media

Laureate Education (Producer). (2016l). The t test for independent samples [Video file]. Baltimore, MD: Author.

Note: The approximate length of this media piece is 5 minutes.

In this media program, Dr. Matt Jones, demonstrates the t Test for independent samples in SPSS.

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

Laureate Education (Producer). (2016m). The t test for related samples [Video file]. Baltimore, MD: Author.

Note: The approximate length of this media piece is 5 minutes.

In this media program, Dr. Matt Jones, demonstrates the t test for related samples in SPSS.

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

Optional Resources

Klingenberg, B. (2016). Inference for comparing two population means. Retrieved from https://istats.shinyapps.io/2sample_mean/

Use the following app/weblink to enter your own data and obtain an interactive visual display.

Skill Builders:

  • Research Design and Statistical Design
  • Hypothesis Testing for Independent Samples t-test

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. 

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