Statistics in Experimental Design (ANOVAs)
Statistics in Experimental Design (ANOVAs)
The course concentrates on the analysis of data obtained from experiments in the behavioral sciences, especially psychology. Major emphasis is placed on analysis of variance techniques going from simple single-factor independent group designs to multiple-factor designs involving both between- and within- subject manipulations. General rules are stressed.
After completing this course, students will be able to:
Think critically about the application of experimental and quasi-experimental designs in psychological research
Use computers to conduct analyses and interpret their output
Understand and apply appropriate statistical analyses for different types of experimental designs
Apply data analysis skills to research in different areas of psychology
Keppel, G., & Wickens, T. D. (2004). Design and Analysis: A Researcher's Handbook (4th ed.). Upper Saddle River, NJ: Pearson Prentice Hall. (available at Norris Center bookstore).
Other assigned articles or handouts available through this web site or in class
Tuesdays and Thursdays: 9:30 - 10:50 AM
Harris - Room 205
An objective midterm exam near the middle of the term (October 21)
An objective final exam (during the university final exam period)
Weekly homework sets (Posted and due each Thursday starting the second week of class)
Homework - 40%
Midterm Exam - 30%
Final Exam - 30%
The documents below are in PDF format. You will need a reader program, such as Adobe Acrobat to read them. If you do not have such a program, a free version is available here
If you woud like to print multiple pages of the PDF file onto one printer page, here are instructions for some printers (note that some slight modification might be required depending on printer used):
When in the PDF, click on the printer icon at the top of the page
Click on the PROPERTIES button in the box that has appeared
Change the PAGES PER SHEET to be whatever you prefer
Click OK on the box that you made pop up by hitting PROPERTIES
Click OK on the box that you made pop up by hitting the printer icon
You will be abe to save considerable pages this way and still use the PDF format.
Problem Sets and Data
Introduction to the course
Comparing F distributions with other distributions
Comparison of ANOVA with other methods
Problem Set #1
SPSS Data #1
Assumptions made by the ANOVA
What to do when the assumptions don't hold
Meaning of positive and negative results
Data Set for 10/5
Output from data set for 10/5
Tukey's Ladder of Powers Handout
Tabachanick and Fidell recommendations
Problem Set #2
Anaytic, Planned Comparisons
Problem Set #3
Midterm Examination - Thursday
Introduction to Factorial Design
Two Factor Designs
Main Effect Calculations
More on Main Effects
Problem Set #4
More on Interactions and Calculations
General Linear Model
Unequal Sample Sizes
Problem Set #5
Analysis of Covariance
Single Factor Within Subjects Design
Problem Set #6
Further Within Subjects Topics
Two-Factor Within-Subjects Designs
Problem Set #7 - Due Tuesday, 11/30
Mixed Design: Overall Analysis
No Class Thursday - Thanksgiving
Mixed Design: Analytical Analyses
Catch Up / Review / Further Topics
Chapter 26 (?)
Monday, December 6, 2004
12:00 - 2:00 P.M.
Cohen, J. (1992). A power primer. Psychological Bulletin, 112, 155-159.
Tukey, J. W. (1977). Exploratory Data Analysis. Reading, MA: Addison-Wesley Publishing Company.
Tabachnick, B. G., & Fidell, L. S. (1996). Using Multivariate Statistics. (3rd ed.). New York: Harper Collins.
Wilkinson, L., & APA Task Force on Statistical Inference. (1999). Statistical methods in psychology journals: Guidelines and explanations. American Psychologist, 54, 594-604.
Work Mentioned in Class:
Cohen, J. (1962) The statistical power of abnormal-social psychological research: a review. Journal of Abnormal and Social Psychology 69, 145-153.
Cohen, J. (1988) Statistical Power Analysis for the Behavioral Sciences. (2nd ed). Mahwah, NJ: Lawrence Erlbaum.
Some Other Useful Resources with Information on Statistics in Experimental Design:
Abelson, R. P. (1995). Statistics as Principled Argument. New Jersey: Lawrence Erlbaum Associates.
Hays, W. L. (1994). Statistics (5th ed.). Fort Worth, TX: Harcourt Brace College Publishers.
Howell, D. C. (2001). Statistical Methods for Psychology (5th ed.). Belmont, CA: Duxbury Press.
Kirk, R. E. (1995). Experimental Design: Procedures for the Behavioral Sciences. (3rd ed.). Pacific Grove, CA: Brooks/Cole.
Kuehl, R. O. (2000). Design of Experiments: Statistical Principles of Research Design and Analysis (2nd ed.). Pacific Grove, CA: Duxbury Press.
Maxwell, S. E., & Delaney, H. D. (2004). Designing Experiments and Analyzing Data: A Model Comparison Perspective. (2nd ed.). Mahwah, NJ: Erlbaum.
Neter, G., Kutner, M. H., Nachtsheim, C. J., & Wasserman, W. (1996). Applied linear statistical models (4th ed.). Boston, MA: McGraw-Hill.
Pedhauzer, E. J., & Pedhauzer Schmelkin, L. (1991). Measurement, Design, and Analysis: An Integrated Approach. Hillsdale, NJ: Erlbaum.
Rosenthal, R., & Rosnow, R. L. (1991). Essentials of Behavioral Research: Methods and Data Analysis (2nd ed.). Boston, MA: McGraw-Hill.
Schinka, J. A., & Velicer, W. F. (2003). Handbook of Psychology - Volume 2: Research Methods in Psychology. Hoboken, NJ: John Wiley.
Winer, B. J., Brown, D. R., & Michels, K. M. (1991). Statistical Principles in Experimental Design (3rd ed.). Boston, MA: McGraw-Hill.