Graduate Courses in Quantitative Psychology
6810 Statistical Methods in Psychology I (4): Topics include basic concepts of descriptive and inferential statistics, estimation, hypothesis testing, non-parametric techniques, and analysis of variance. Autumn 2025, 2026, 2027: Dr. Van Zandt
6811 Statistical Methods in Psychology II (4): Topics include simple linear regression and correlation, multiple linear regression, interactions, and introduction to other related methods such as nonlinear regression and random effects models. Spring 2025, 2026, 2027: Dr. Pek
6820 Introduction to Bayesian Statistics for Psychological Data (3): Topics include basic probability and Bayes theorem, inference from the modern Bayesian perspective focusing on analysis of proportions and means, interval estimates, regression, and Bayes factors. Spring 2027: Dr. Van Zandt
6822 Statistical Mediation, Moderation, and Conditional Process Analysis (3): Topics include classic and contemporary approaches to testing mediation and moderation hypotheses, path analysis, indirect and direct effects, probing and plotting interactions, and analytically integrating moderation and mediation analysis. Permission of the instructor may be required. Fall 2025: Dr. Pek
6863 Psychometrics (3): Topics include classic and contemporary psychological measurement, test construction, reliability, validity, norming, and the APA and AERA Standards for educational and psychological testing. Permission of the instructor may be required. Spring 2025, 2027: Dr. Pek & Dr. Walton
7695.06 Seminar in Quantitative Psychology (1-3):
7820 Fundamentals of Factor Analysis (3): Topics include principal component analysis, exploratory factor analysis, and confirmatory factor model models, and relevant statistical software for those three approaches. Specific topics include estimation methods, factor rotation, factor scores, measurement invariance, and goodness of fit. Permission of the instructor may be required.
7821 Covariance Structure Models (3): Topics include the general structural equations model and specific variants, identification, parameter estimation, goodness of fit, model modification, and use of relevant statistical software. Permission of the instructor may be required. Spring 2025: Dr. Cho
7822 Fundamentals of Item Response Theory (3): Topics include the theory and hands-on use of generalized linear mixed models for categorical data and explanatory measurement models, unidimensional and multidimensional measurement models, item and test information, score dependent reliability, detection of violations such as differential item functioning and local dependence. Permission of the instructor may be required.
7823 Analysis of Repeated Measures and Longitudinal data (3): Topics include statistical methods for the analysis of nested data with focus on repeated measures, longitudinal studies, and change over time. Permission of the instructor may be required. Spring 2026 & Autumn 2027: Dr. Pek
7896 Special Topics in Quantitative Psychology (2): This course runs over the Autumn and Spring semesters that features research and professional development talks relevant to quantitative psychology. This course required for all quantitative psychology students.
8896 Advanced Seminar in Quantitative Psychology (3):
Power analysis. Topics include effect size determination, different approaches to computing power (e.g., R pwr package, G*power, SAS PROC POWER, Monte Carlo simulation); misconceptions, limits, and abuses of power analysis. Permission of the instructor may be required.
Undergraduate Courses in Quantitative Psychology
2220 Data Analysis in Psychology (3): Prerequisites: 1100 (100) or 1100H (100H), and Statistics 1450 (145), Math 1130, Math 1148 (148), Math 1149, 1150 (150), 1151 (151), or 152, or equivalent, or Math Placement Level M or higher; or permission of instructor. Not open to students with credit for 220, 220H, 320, or 320H. This course is available for EM credit. Topics include random samples, graphical and numerical techniques of descriptive statistics, correlation, regression, probability, sampling distribution, and hypothesis testing.
2220H Data Analysis in Psychology (Honors) (3): Prerequisites: Honors standing, and 1100 (100) or 1100H (100H), and Statistics 1450 (145), Math 1130, Math 1148 (148), Math 1149, 1150 (150), 1151 (151), or 152, or equivalent, or Math Placement Level M or higher; or permission of instructor. Not open to students with credit for 2220 (220), 220H, 320, or 320H. Topics include random samples, graphical and numerical techniques of descriptive statistics, correlation, regression, probability, sampling distribution, and hypothesis testing. Autumn 2025, 2026, 2027: Dr. Cho
3321 Quantitative and Statistical Methods in Psychology (3): Prerequisites: 1100 (100) or 1100H (100H), and a grade of B or above in 2220 (220) or 2220H (220H). Not open to students with credit for 321 or 321H. Topics include applications of statistical tools in inference in contemporary psychology, hypothesis testing, regression, correlation, and analysis of variance. Spring 2025: Dr. Spencer
3321H Quantitative and Statistical Methods in Psychology (Honors) (3): Prerequisites: Honors standing, and 1100 (100) or 1100H (100H), and a grade of B or above in 2220 (220) or 2220H (220H). Not open to students with credit for 321 or 321H. Topics include applications of statistical tools in inference in contemporary psychology, hypothesis testing, regression, correlation, and analysis of variance. Spring 2025: Dr. Van Zandt
4511 Psychological Testing (3): Prerequisites: Grade of C- or above in 2220 and 2300. Not open to students with credit for 511 or 597.02. Topics include theoretical and practical aspects of the assessment and prediction of human behavior, focusing on achievement, intelligence, personality, attitudes, interests, and interpersonal relations. Fall 2024, 2026: Dr. Walton & Dr. Pek