PSY 530 Analysis of Variance
Announcements | Goals | Required Books | Course Requirements | Assignments | Exams Last updated 09/14/2004
GoalsAt the end of the course I expect that you will: 1. be able to compute a variety of ANOVA designs by hand. Keppel, G. & Wickens, T. D. (2004). Design and Analysis: A researchers handbook (Fourth Edition) . Englewood Cliffs, New Jersey: Prentice Hall. Page, M. C., Braver, S. L., & MacKinnon, D. P. (2003). Levine's Guide to SPSS for Analysis of Variance (Second Edition) . Hillsdale, NJ: Lawrence Erlbaum. Readings on special topics will be available in the Graduate Reading room. Optional: Abelson, R. P. (1995). Statistics as a Principled Argument . Hillsdale, NJ: Lawrence Erlbaum. 1. Exams There will be three exams during the course and a final exam. Grading 1. Exams during the semester 54% Active and Cooperative Learning This class will employ active learning strategies. The purpose of these methods is to engage students in a way that increases retention of the material. It is also more fun and less boring than more traditional lecture-only formats. These strategies will include splitting students into groups of two to five persons. Resources The instructor and teaching assistant will be available during office hours. Students are also encouraged to study in small groups and to use any available resources to increase their learning in the course. Some of these resources include other books on analysis of variance, other graduate students, faculty members, and self-study books. Computer Work Students will learn how to conduct ANOVA analyses using the Statistical Analysis System (SAS) and Statistical Programs for the Social Sciences (SPSS) computer software. We will use the statistical computing laboratory in room 153 in the Psychology Building. You will be instructed in how to logon and use this system. The computer work for the course will be writing and running programs and interpreting output. Syllabus The course will cover analysis of variance (ANOVA) including between subjects, within subjects, mixed designs and designs with random factors. Analysis of variance is the most commonly used analysis method for experimental data in the social sciences. Students will learn the theoretical rationale and methods to compute analysis of variance by hand and with computer software. MS Word Version. August 24 and 26 (HW1 Out) Introduction, History, Research Design, Variability August 31 and September 2 (HW1 In; HW2 Out) Sampling Distributions, One-way Between Subjects ANOVA, Analytical Comparisons September 7 and 9 (HW2 In; HW3 Out) Analytical comparisons and Trend Analysis September 14 and 16 (HW3 In: Review Questions Out) Correction for Experimentwise Error Rates, Assumptions, Review September 21 and 23 (HW4 Out) Assumption, Effect Size, and Power First Exam September 21 September 28 and 30 (HW4 In; HW5 Out) Effect Size and Power, Two Factor Design October 5 and 7 (HW5 In; HW6 Out) Factorial Design October 12 and 14 (HW6 In; Review Questions Out) Detailed Analysis of Main Effects and Simple Effects Second Exam October 19 October 26 and 28 (HW7 In; HW8 Out) The General Linear Model, Unequal Sample Sizes, and the Within-Subjects Design November 2 and 4 (HW8 In; HW9 Out) Within-subjects Designs continued November 9 (HW 9 In; Review Questions Out) and 11 (Veteran's Day, No class) Mixed Designs November 16 and 18 (HW10 Part I Out) Mixed Designs continued and Higher-order designs Third Exam November 16 November 23 (HW10 Part II Out) and 25 (No Class, Thanksgiving) Higher order designs and Special Topics November 30 and December 2 (HW10 In; Review Questions Out) Higher order designs and Special Topics December 7 Special Topics and Review Final Exam Thursday December 9 7:40-9:30 *Note: The syllabus may change.
Examples and Computer Handouts
Running
Programs - Step by step ANOVA BooksBogartz, R. S. (1994). An Introduction to the Analysis of Variance. Westport, Connecticut: Praeger. Box, J. F. (1978). R. A. Fisher, the life of a scientist. New York: Wiley. Written by Fisher's daughter. *Cortina, J. M. & Nouri, H. (2000). Effect size for ANOVA designs . Thousand Oaks, CA: Sage. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2 nd ed.). Hillsdale, NJ: Erlbaum. Classic power book. Crowder, M.J. and Hand, D.J. (1990). Monographs on Statistics and Applied Probability 41: Analysis of repeated measures . New York : Chapman and Hall. Edgington, E. S. (1986). Randomization tests (2 nd ed.). New York: Marcel Dekker. Edwards, A. L. (1979). Multiple regression and the analysis of variance and covariance . San Francisco: Freeman. ANOVA in regression models. Edwards, L. K. (Ed.) (1993). Analysis of Variance in the Behavioral Science . New York: Marcel Dekker. Chapters by different authors on current issues in analysis of variance. Fienberg, S.E. & Hinkley, D.V. (1980). R.A. Fisher: An appreciation . New York: Springer-Verlag. Call #QA276.16.r18 Science Library). Chapters by different authors on Fisher's contributions to many areas of statistics. Fisher, R. A. (1925). Statistical methods for research workers . Edinburgh: Oliver and Boyd. First book on ANOVA. Fisher, R. A. (1935). The design of experiments. Edinburgh: Oliver and Boyd. First book on design. Fisher, R. A. (1959). Statistical Methods and Scientific Inference . New York: Hafner. Call #QA9F54. Classic book more focused on inference and design rather than ANOVA. Clear explanations of many. Hand, D.J. & Taylor, C.C. (1991). Multivariate analysis of variance and repeated measures . New York: Chapman and Hall. Hays, W. L. (1973). Statistics for the social sciences . New York: Holt, Rhinehart, and Wilson. Iverson, G.R. & Norpoth, H. (1976). Analysis of Variance : Sage University Paper series on Quantitative Applications in the Social Sciences. 07-001. Beverly Hills and London: Sage. *Jackson, S. & Brashers, D.E. (1994). Random factors in ANOVA. Thousand Oaks, CA:Sage. Keppel, G. (1991). Design and analysis: A researcher's handbook (3 rd ed.) . Englewood Cliffs, New Jersey: Prentice-Hall. Clear substantive and quantitative introduction to analysis of variance. Keppel, G. & Zedeck, S. (1989). Data analysis for research designs: Analysis of variance and multiple regression/correlation approaches . New York: W.H. Freeman. Covers both ANOVA and regression based analysis for experimental and nonexperimental designs. *Kirk, R.E. (1995). Experimental Design: Procedures for the Behavioral Sciences. Pacific Grove, CA: Brooks/Cole. Excellent book. Good section on transformations. Mason, R. L., Gunst, R. F., & Hess, J. L. (1989). Statistical design & analysis of experiments , New York: Wiley. Mead, R. (1991). The design of experiments: Statistical principals for practical application . Cambridge, UK: Cambridge University Press. Linear models approach to ANOVA. Good resource. *Murphy, K. R. & Myors, B. (1998). Statistical power analysis: A simple and general model for traditional and modern hypothesis tests . Hillsdale, NJ: Erlbaum. General way to compute power based on the noncentral F. *Rosenthal, R., Rosnow, R. L., & Rubin, D. B. (2000). Contrasts and effect sizes in behavioral research: A correlational approach . Cambridge, UK: Cambridge University Press. Salsburg, D. (2001). The lady tasting tea: How statistics revolutionized science in the twentieth century. Freeman: New York. Good overview of statistics. Scheffe, H. (1959). The Analysis of Variance , New York: Wiley. Call #QA 276.S34 Science Library. Classic and mathematically sophisticated book. Winer, B.J., Brown, D.R., & Michels, K.M. (1991). Statistical Principles in Experimental Design (3 rd Edition) . New York: McGraw-Hill. Excellent book. Good resource. The third edition by the last two authors was completed after Winer died. *Woodward, J. A., Bonett, D.G. & Brecht. M.L. (1990). Introduction to linear models and experimental design , : New York : Harcourt Brace Jovanovich. Excellent book describing the linear model approach to ANOVA. *books which were considered for Psy 530. |
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