EPSE 592: Experimental Design & Analysis
2021/22, Winter Term 1
Course overview:
This course will cover all the basics and essentials of experimental design and analysis. These methods have a long history and enjoy broad application in all of the natural, social, and health sciences. We will discuss theory and applications. Mathematical foundations will form a component of the material, though our main focus will be on practical applications for researchers in a variety of disciplines.
Recommended textbooks:
- Fundamental Concepts in the Design of Experiments, Charles R. Hicks & Kenneth V. Turner, Jr. This is a superb textbook. It contains most of the relevant mathematics of the subject, but takes a very conversational and example-driven approach throughout.
- Analysis of Variance Designs, Glenn Gamst, Lawrence S. Meyers, & A.J. Guarino. A soft textbook written for social scientists. Very light on mathematical details, but many informative examples and case studies.
-Statistical Methods for Psychology, David C. Howell. A nice compromise text between the previous two in terms of technical content. An online copy can be found here.
Class Notes:
-Week 1: Introduction and Stats Review 1 (random variables, statistics, standard errors, confidence intervals, Central Limit Theorem)
-Week 2: Stats Review 2 (conditional probability, p-values, Bayes' Theorem, t-tests, F-tests)
-Week 3: Type I/II errors, multiple testing problem
-Week 4: One-way Analysis of Variance (ANOVA)
-Week 5: Assumptions of the ANOVA model and diagnostics; two-way ANOVA
-Week 6: Interaction effects; n-way ANOVA, measures of effect size
-Week 7: Statistical power
-Week 8: Unbalanced ANOVA; restricted randomization
-Week 9: Repeated measures ANOVA
-Week 10: Analysis of Covariance (ANCOVA)
-Week 11: Nonparametric tests: Mann-Whitney, Kruskal-Wallis, Wilcoxon signed-rank
-Week 12: Categorical data analysis: Chi-squared tests, Fisher's exact test
-Week 1: Introduction and Stats Review 1 (random variables, statistics, standard errors, confidence intervals, Central Limit Theorem)
- Extra notes on confounding variables from "Handbook of Biological Statistics" (HBS) by John H. McDonald
- Extra notes on probability from HBS
-Week 2: Stats Review 2 (conditional probability, p-values, Bayes' Theorem, t-tests, F-tests)
- Extra notes on standard error of the mean from HBS
- Extra notes on confidence intervals from HBS
- Extra notes on hypothesis testing from HBS
-Week 3: Type I/II errors, multiple testing problem
- Extra notes on t-test from HBS.
- Epstein et al (2020)
- Ma et al (2020)
-Week 4: One-way Analysis of Variance (ANOVA)
-Week 5: Assumptions of the ANOVA model and diagnostics; two-way ANOVA
-Week 6: Interaction effects; n-way ANOVA, measures of effect size
-Week 7: Statistical power
-Week 8: Unbalanced ANOVA; restricted randomization
-Week 9: Repeated measures ANOVA
-Week 10: Analysis of Covariance (ANCOVA)
-Week 11: Nonparametric tests: Mann-Whitney, Kruskal-Wallis, Wilcoxon signed-rank
-Week 12: Categorical data analysis: Chi-squared tests, Fisher's exact test