Lab Manual for Statistical Analysis

Dawn M. McBride is professor of psychology at Illinois State University, where she has taught research methods since 1998. Her research interests include automatic forms of memory, false memory, prospective memory, task order choices, and forgetting. In addition to research methods, she teaches courses in introductory psychology, cognition and learning, and human memory; she also teaches a graduate course in experimental design. She is a recipient of the Illinois State University Teaching Initiative Award and the Illinois State University SPA/Psi Chi Jim Johnson Award for commitment to undergraduate mentorship, involvement, and achievement. Her nonacademic interests include spending time with her family, traveling, watching Philadelphia sports teams (it was a good year for Philly sports this year!), and reading British murder mysteries. She earned her PhD in cognitive psychology from the University of California, Irvine, and her BA from the University of California, Los Angeles. J. Cooper Cutting (PhD, cognitive psychology, University of Illinois at Urbana-Champaign) is associate professor of psychology at Illinois State University. Dr. Cutting's research interests are in psycholinguistics, primarily, with a focus on the production of language. A central theme of his research is how different types of information interact during language use. He has examined this issue in the context of lexical access, within-sentence agreement processes, figurative language production, and pragmatics. He has taught courses in research methods, statistics, cognitive psychology, computer applications in psychology, human memory, psycholinguistics, and sensation and perception. He is also a recipient of the Illinois State University SPA/Psi Chi Jim Johnson Award for commitment to undergraduate mentorship, involvement, and achievement. His non-academic interests include gardening and reading science fiction and fantasy novels.

Preface Introduction for Students Section 1. Topic Activities 1. Statistics in the Media 2. The Purpose of Statistics 3. Understanding Your Data 4. Research Concepts: Designs, Validity, and Scales of Measurement 5. Measurement Group Activity 6. Designing an Experiment Group Activity 7. Experimental Variables 8. Distributions and Probability 9. Displaying Distributions 10. Setting Up Your Data in SPSS: Creating a Data File 11. Displaying Distributions in SPSS 12. Basic Probability 13. Sampling 14. Central Tendency 1 15. Central Tendency 2 16. Central Tendency in SPSS 17. Describing a Distribution by Hand 18. More Describing Distributions 19. Descriptive Statistics Exercise 20. Descriptive Statistics With Excel 21. Measures of Variability in SPSS 22. Calculating z Scores Using SPSS 23. The Normal Distribution 24. z Scores and the Normal Distribution 25. Hypothesis Testing With Normal Populations 26. Stating Hypotheses and Choosing Tests 27. Hypothesis Testing With z Tests 28. Hypothesis Testing With a Single Sample 29. One-Sample t Test in SPSS 30. One-Sample t Tests by Hand 31. Related Samples t Tests 32. Related Samples t Test in SPSS 33. Independent Samples t Tests 34. Hypothesis Testing: Multiple Tests 35. More Hypothesis Tests With Multiple Tests 36. t Tests Summary Worksheet 37. Choose the Correct t Test 38. One-Way Between-Subjects ANOVA by Hand 39. One-Way Between-Subjects ANOVA in SPSS 40. Factorial ANOVA 41. One-Way Within-Subjects ANOVA 42. One-Way Within-Subjects ANOVA in SPSS 43. ANOVA Review 44. Which Test Should I Use? 45. Correlations and Scatterplots Exercise 46. Correlations and Scatterplots 2 47. Correlations and Scatterplots in SPSS 48. Computing Correlations by Hand 49. Computing Correlations by Hand 2 50. Hypothesis Testing With Correlation 51. Hypothesis Testing With Correlation Using SPSS 52. Regression 53. Chi-Square Test for Independence Section 2. Meet the Formulae 54. Meet the Formula: Standard Deviation 55. Meet the Formula: z Score Transformation 56. Meet the Formula: Single-Sample z Tests and t Tests 57. Meet the Formula: Comparing Independent Samples and Related Samples t Tests 58. Meet the Formula: One-Factor Between-Subjects ANOVA 59. Meet the Formula: Two-Factor ANOVA 60. Meet the Formula: One-Factor Within-Subjects ANOVA 61. Meet the Formula: Correlation 62. Meet the Formula: Bivariate Regression Section 3. Data Analysis Projects 63. Data Analysis Exercise: von Hippel, Ronay, Baker, Kjelsaas, and Murphy (2016) 64. Data Analysis Exercise: Nairne, Pandeirada, and Thompson (2008) 65. Data Analysis Project 1: Crammed Versus Distributed Study 66. Data Analysis Project 2: Teaching Techniques Study 67. Data Analysis Project 3: Distracted Driving Study 68. Data Analysis Project 4: Temperature and Air Quality Study 69. Data Analysis Project 5: Job Type and Satisfaction Study 70. Data Analysis Project 6: Attractive Face Recognition Study 71. Data Analysis Project 7: Discrimination in the Workplace Study Section 4. How to Choose a Statistical Test 72. Using the Flowchart to Find the Correct Statistical Test 73. More Using the Flowchart to Find the Correct Statistical Test 74. Research Design Exercise 75. Design and Data Collection Exercise 76. Designs and Analyses Section 5. Describing and Interpreting Results in APA Style 77. Writing a Results Section From SPSS Output: t Tests 78. Writing a Results Section From SPSS Output: ANOVA 79. Interpreting Results Exercise: Sproesser, Schupp, and Renner (2014) 80. Interpreting Results Exercise: Ravizza, Uitvlugt, and Fenn (2017) Appendix: Summary of Formulae References

"The lab manual is well thought out and contains appropriately related examples. My students would find these examples useful as practical applications." -- Michael Ray "The activities are easy to follow and relatively short. I like the inclusion of suggestions for group work-it would be nice to be able to use these in class. I would definitely have the lab manual as a required companion." -- Courtney McManus