Dr. Kimberly Neuendorf’s Research Methods & Statistics Materials

Sample Multivariate Analyses Syllabus

INTRO:

1. Selecting Appropriate Statistics (from Neuendorf’s Content Analysis Guidebook (2017, 2nd ed.))

2. Levels of Measurement (PPT)

3. The Variate (PPT)

4. Intro to SPSS (PPT)

5. Degrees of Freedom (PPT)       

REVIEW:

6. Questionnaire Construction

7. Normal Curve Areas

8. Probability

9. Combinations and Permutations

10. Power, Type I and Type II Error

11. Standard Deviation

12. Standard Error and Confidence Intervals

13. The Chi-Square

14. The t-test

14a. Why ANOVA?

15. Bivariate Correlation

16. Covariance/Correlation (partly from Blalock)

17. Linear Regression

AFTER REVIEW:

18. Scale Construction

19. Reliability and Validity

20. Cronbach’s alpha (from Carmines & Zeller)

21. Internal Consistency Reliability (Can Cronbach’s Alpha be Too High?)

22. Two-factor ANOVA (from Williams)

23. Eta squared (from Tabachnick & Fidell)

24. Four Moments (PPT)

25. Moments about the Mean

26. Homoscedasticity/Heteroscedasticity (PPT)

27. Transforming Data

28. Mediating vs. Moderating Variables

29. Controlling for a Third Variable (i.e., Checking for Mediation)

30. Factor Analysis

31. Multiple Regression:  Beginnings

32. Multiple Regression

33. Multiple Regression Tabling–Examples

34. Condition Index (Checking Multicollinearity) (from Hair et al., 5th ed.)

35. Adjusted R-squared (from Cohen & Cohen)

36. Dummy and Effect(s) Coding

37. Power for Partial Coefficients (from Cohen & Cohen)

38. Discriminant Analysis

39. Logistic Regression

40. MANOVA/MANCOVA

40a. The ANOVA Family

41. Post Hoc Tests (a primer)

42. Canonical Correlation

43. Cluster Analysis

44. Multidimensional Scaling

45. Structural Equation Modeling

45a. SEM with AMOS–Examples

46. Optional reading: Diamond, J. (1987, August). Soft sciences are often harder than hard sciences. Discover, pp. 34-35, 38-39.

47. Optional reading: “Matrix Algebra” (from Pedhazur)

48. Optional reading: Data Transformation and Selection–RECODE and COMPUTE syntax for SPSS

49. Optional reading: SPSS Data Transformation Syntax–Some Examples

50. Optional reading: Pencil, M. (1976). Salt passage research: The state of the art. Journal of Communication26(4), 31-36.
 
51. Optional reading: Fink, E. L. (2009). The FAQs on data transformation. Communication Monographs76, 379-397.

52. Optional reading: Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology51, 1173-1182. 

2019 In-Class Presentations

1. Dr. N presents “Factor Analysis”

Factor Analysis Table Example (editable version available for download)

2. Tyler presents “Multiple Regression”

Multiple Regression Table Example (editable version available for download)

3. Helen presents “Discriminant Analysis”

Discriminant Analysis Table Example (editable version available for download)

4. Itza presents “Logistic Regression”

Logistic Regression Table Example (editable version available for download)

5. Dr. N presents “Two-factor ANOVA”

Two-factor ANOVA Table Example (editable version available for download)

6. Danny presents “MANOVA”

MANOVA Table Example (editable version available for download)

MANCOVA In-class Example (Dr. N.)

6. Matt presents “Cluster Analysis”

Cluster Analysis Table Example (editable version available for download)

2018 In-Class Presentations

1. Dr. N presents “Factor Analysis” (3/5/18)

Factor Analysis Table Example (editable version available for download)

2. Samantha and Dennessa present “Multiple Regression” (3/26/18)

Multiple Regression Table Example (editable version available for download)

3. Marcy and Jennifer present “Discriminant Analysis” (4/2/18)

Discriminant Analysis Table Example (editable version available for download)

4. Matt and Ambrosia present “Logistic Regression” (4/9/18)

Logistic Regression Table Example (editable version available for download)

5. Dr. N presents “Two-factor ANOVA” (4/9/18)

Two-factor ANOVA Table Example (editable version available for download)

6. Krista and Sonoyta present “MANOVA/MANCOVA” (4/16/18)

MANOVA Table Example (editable version available for download)

7. 2017 In-Class Presentations

1. Dr. N presents “Factor Analysis”

2. Doris presents “Multiple Regression-Hierarchical”

3. Olivia presents “Multiple Regression-Stepwise”

4. Alissa presents “Discriminant Analysis”

5. Ibrahim presents “Logistic Regression (Single Block)”

6. Kristi presents “Logistic Regression (Multiple Blocks, with Stepwise)”

7. Dr. N presents “Two-factor ANOVA/ANCOVA”

8. Shantale and Marisha present “MANOVA”

9. Shantale and Marisha present “MANCOVA”

10. Lauren and Maria present “Cluster Analysis”

2016 In-Class Presentations

1. Dr. N presents “Factor Analysis”

2. Dr. N presents “Multiple Regression-Hierarchical”

3. Rikki presents “Multiple Regression-Stepwise”

4. Devin presents “Discriminant Analysis”

5. Violet presents “Logistic Regression”

6. Dr. N presents “Two-factor ANOVA/ANCOVA”

7. Carlina presents “MANOVA/MANCOVA”

8. Dania presents “Cluster Analysis”

2014 In-Class Presentations

1. Dr. N presents “Factor Analysis”

2. Arthur and Bo present “Multiple Regression-Hierarchical”

3. Arthur and Bo present “Multiple Regression-Stepwise”

4. Kyle and Marlin present “Discriminant Analysis”

5. Tim and Cat present “Logistic Regression”

6. Dr. N presents “2-Factor ANOVA”

7. Paul and Kaila present “MANOVA/MANCOVA”

8. Christopher presents “Canonical Correlation”

9. Amelia and Cat present “Cluster Analysis”

10. Dr. N presents “Multidimensional Scaling (MDS)”

11. Changhyun and Mark present “Structural Equation Modeling (SEM)”

2013 In-Class Presentations

1. Dr. N presents “Factor Analysis”

2. Joe presents “Multiple Regression-Stepwise”

3. Hocheol presents “Multiple Regression-Hierarchical”

4. Chichang & Kelly present “Discriminant Analysis”

5. Serineh & Pat present “Logistic Regression”

6. Dr. N presents “2-Factor ANOVA”

7. Congrong presents “MANOVA”

8. Daniel presents “MANCOVA”

9. Jonathan presents “Canonical Correlation”

10. Fran & Jennie present “Cluster Analysis”

11. Jarrett & Jordan present “Multidimensional Scaling (MDS)”

12. Dr. N and class present “Structural Equation Modeling (SEM)”

2011 In-Class Presentations

1. Jeff presents “Factor Analysis”

2. Dorigen presents “Multiple Regression”

3. Elizabeth and Kelly present “Discriminant Analysis”

4. Rachel & Matt E. present “Logistic Regression”

5. Ben & James present “MANOVA/MANCOVA”

6. Joan presents “Canonical Correlation”

7. Sean & Matt M. present “Cluster Analysis”

8. Mike & Dr. Skalski present “Multidimensional Scaling (MDS)”

9. Aaron & Dr. Neuendorf present “Structural Equation Modeling (SEM)”

10. Rod Antilla’s (ABR Research) PowerPoint Presentation on “Conjoint Analysis)

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