PSY610: PSYCHOMETRICS/

FALL, 2006

Dr. Gregory T. Smith Teaching Assistant: 105 Kastle Hall Lauren Gudonis 257-6454 [email protected] [email protected] office: 111 J

Office Hours: Monday and Wednesday 11:00 - 11:45 and by appt.

Required Texts:

1. Keppel, G. (2004). Design and Analysis: A Researcher’s Handbook. (4th Edition). Upper Saddle River, N.J.: Pearson/Prentice-Hall, Inc.

Course Outline

8/24 1. Introduction. Independent and dependent variables. Correlational and experimental studies. Implications for interpretation of results. Example. and Random .

8/29 2. Levels of . Examples. Relation of levels of measurement to statistical tests. Chart. Three major questions to be answered by statistical analysis: existence, nature, and magnitude of relationships between X and Y (or Y1 and Y2). Introduction to probability.

8/31 3. Probability: an intuitive approach and a formal approach. Independence and conditional probabilities. Introduction to the logic of hypothesis testing.

9/5 4. The logic of hypothesis testing. Introduction to parametric (normal distribution) techniques. One z. of the . . of the mean.

Lab #1 Introduction to lab. Probability. Definitions, examples, and exercises. Introduction to computer system. Homework #1 assigned.

9/7 5. Logic of hypothesis testing, decision rule, terms, power, Type I and Type II errors.

9/12 6. Student's t test: sampling distribution, procedures, assumptions, degrees of freedom. Unbiased and biased estimates. Directional v. nondirectional tests, confidence intervals, t and z compared. Lab #2 Review material from preceding two lectures; homework; SPSS exercises.

9/14 7. Factors affecting power, Effect sizes, independent and dependent samples t-test

9/19 8. Review of both z’s and all three t’s. Introduce nonparametric tests.

Lab #3 Review material from preceding two lectures; homework; SPSS exercises.

9/21 9. Mann-Whitney U test, Wilcoxon signed ranks test, test, .

9/26 10. Mann-Whitney U test, Wilcoxon signed ranks test, Median test, Sign test.

Lab #4 Review material from preceding two lectures; homework; SPSS exercises.

9/28 11. Chi-Square goodness of fit; review for Exam I

10/3 12. Chi-square test of independence, review with chart.

Lab #5 Exam I (covers material up to, but not including, chi-square)

10/5 13. Introduction to Analysis of (ANOVA) and the F test. Assignment: Read Keppel chaps. 5.1, 6

10/10 15. Continue discussion of simple randomized design (SRD), begin discussion of Contrasts. Assignment: Keppel, chaps. 7 and 8

Lab #6 Review Exam I. Review material from preceding two lectures; homework; SPSS exercises

10/12 16. Contrasts: planned comparisons and trend tests for the SRD.

10/17 17. Post-hoc tests: Newman-Kuels, Tukey a and b tests, Scheffe test. Assignment: Keppel, Chap. 4.

Lab #7 Review material from preceding two lectures; homework; SPSS exercises

10/19 18. Complete post-hocs. Assumptions. Nonparametric analogue: Kruskal-Wallis test. Power: estimating power, using sample size to control for power. Assignment: Keppel, Chaps. 9 and 10

10/24 19. Introduction to the Factorial Design (FD): the case of two independent variables. Rationale and the concept of . Sources of variance. Assignment: Keppel, Chaps. 11 and 12.

Lab #8 Review material from preceding two lectures; homework; SPSS exercises.

10/26 20. FD: continued discussion of computation. Analysis of main effects and simple effects. Begin discussion of interaction contrasts, trend tests, and post hocs. Assignment: Keppel, Chap. 13.

10/31 21. FD: continued discussion of interaction contrasts, trend tests, and post hocs. Orthogonality and issue of unequal sample sizes. Assumptions. Assignment: Keppel, Part IV introduction and Chap. 14.

Lab #9 Review material from preceding two lectures; homework; SPSS exercises

11/2 22. Complete discussion of FD, trends, interactions, post hocs, unequal cell sizes, and assumptions.

11/7 23. The Randomized Blocks Design (RBD). Rationale and relation to FD. The Analysis of (ANCOVA): regression, rationale, procedure.

Lab #10 EXAM II (includes all material covered through lab 10)

11/9 24. Continued discussion of ANCOVA and RBD. Assumptions. RBD v. ANCOVA. Assignment: Keppel, Chaps. 15 and 16

11/14 25. Introduction to within-subjects (repeated measures) designs. Crossing subjects with factors. Introduction to the single-factor (RMD). Terminology, sources of variance, expected mean squares.

Lab #11 Review Exam II. Review material from preceding two lectures; homework; SPSS exercises

11/16 26. Assumptions of RMD analysis. Planned comparisons and trend tests. Post-hoc tests. Nonparametric analogue: the . Assignment: Keppel, Chaps. 17 and 18.

11/21 27. The Mixed Design (MD): combining between-subjects and within-subjects factors. Rationale, sources of variance, analyzing main and simple effects.

Lab #12 Review material from preceding two lectures; homework; SPSS exercises

11/28. MD: analysis of interaction effects, planned comparisons, trend tests. Assumptions: compound symmetry. Assignment: Keppel, Chaps. 19 and 20

Lab #13 Review material from preceding lecture; homework; SPSS exercises

11/30 29. Introduction to the Three Factor Design (3-way FD). Components, 3-way interaction, analyzing simple effects. Assignment: Keppel, Chap. 21.

12/5 30. Introduction to the two-factor Repeated Measures Design: overview, main effects, simple effects, interactions.

Lab #14 Review material from preceding two lectures; homework; SPSS exercises

12/7 31. Complete discussion of two-factor repeated measures design; review of course

12/12 EXAM III: 10:30 a.m.

General Information for PSY610

A. The text. There is one basic text (Keppel); it has been assigned for two . First, reading it will help you to follow the lectures and will give you detailed information not covered in the lectures. Second, it will serve as a reference for you during your professional careers.

B. Exams. There will be three exams, as outlined in the course schedule above. They are not cumulative, except in the sense that any math or statistics course is cumulative: you need the earlier concepts to understand the later ones, and earlier concepts are sometimes part of later concepts. The exams will be given during the lab period. I will announce their format as we get closer to them.

C. Assignments. You will be graded on any and all homework assignments. These will include hand computational exercises, sample problems to prepare for exams, and computer exercises. Although they will represent only a small proportion of your grade directly, doing them will be crucial to your success on exams.

D. Grades. Grades will be computed as follows: Exam I = 30%; Exam II = 30%; Exam III = 30%; Homework Assignments = 10%.

E. Attendance Policy. Because this is graduate school, it is taken as a given that you will attend each class period and each lab session.

F. Lab. You are always encouraged to ask questions, but lab is an especially good time to clarify confusing points or review material covered swiftly during lecture. You will learn things in lab that you must know for exams.