The Department of Psychology offers several courses in quantitative methods. Many students seek out elective courses beyond program requirements and may choose to complete a Concentration in Quantitative Methods. Upcoming opportunities for continuing education (e.g., power analysis workshop, Quant Club training events) are posted on our calendar.
Psychology 931: Quantitative Methods for the Behavioral Sciences I
- Usual Instructor: Ashley Votruba
- Pre-Requisites: Instructor permission
- Course Format: 3 credit hours; lecture activity
- Notes: PSYC 931 is offered every fall for first-year psychology graduate students
- Description: This course is the first course in a two-course sequence focused on quantitative methods for the behavioral sciences that (1) build a foundational understanding of quantitative methods used in behavioral science and (2) provide the necessary background for more advanced methods and statistics courses. After completing this course, you will understand the fundamentals of statistics and hypothesis testing, as well as be able to describe the assumptions, report on, and code in a statistical program for t-tests and analysis of variance.
Psychology 932: Quantitative Methods for the Behavioral Sciences II
- Usual Instructor: Jenna Finch
- Pre-Requisites: PSYC 931 and instructor permission
- Course Format: 3 credit hours; lecture activity
- Notes: PSYC 932 is offered every spring for first-year psychology graduate students
- Description: This course is the second course in a two-course sequence focused on quantitative methods for the behavioral sciences that (1) build a foundational understanding of quantitative methods used in behavioral science and (2) provide the necessary background for more advanced methods and statistics courses. After completing this course, you will be able to describe the assumptions, report on, and code in a statistical program for correlations and regression models.
Psychology 948: Structural Equation Modeling in the Behavioral Sciences
- Usual Instructor: Becca Brock
- Pre-Requisites: PSYC 931/932 (or equivalent) and instructor permission. Please email the instructor for a permission code when registration opens.
- Course Format: 3 credit hours; lecture activity
- Notes: PSYC 948 is usually offered every spring
- Description: Fundamentals and foundations of SEM (model specification and identification, data preparation, model estimation, model respecification, reporting results) and specific applications of path analysis (moderation, mediation, and moderated mediation) and latent variable modeling (standard and nonstandard CFA models, integrating latent variables into path models, multiple group analysis).
Psychology 944: Multilevel Modeling in the Behavioral Sciences
- Instructor: Changsoo Song
- Pre-Requisites: PSYC 931/932 (or equivalent) and instructor permission. Please email the instructor for a permission code when registration opens.
- Course Format: 3 credit hours; lecture activity
- Notes: Next offering is spring 2024
- Description: Applications of the multilevel model (hierarchical linear model, general linear mixed model) for analyzing nested data with a particular focus on longitudinal data analysis.
PSYC 971: Data Science and Visualization in R
- Usual Instructor: Jeff Stevens
- Pre-Requisites: None
- Course Format: 3 credit hours; lecture activity
- Notes: Next offering is spring 2025
- Description: Introduction to the fundamental concepts and methods used in the R statistical software package to prepare, visualize, and disseminate data.
Complementary Courses in Qualitative Methods:
Psychology 930: Seminar in Psychometric Methods (Qualitative Methods and Analysis)
- Instructor: Kathryn Holland
- Pre-Requisites: Instructor permission; Please email the instructor for a permission code when registration opens.
- Course Format: 3 credit hours
- Notes: This course will be given a new name and number in the future and will be offered again during the 24-25 academic year.
- Description: Fundamentals of qualitative research methods and analysis, including epistemology and methodology (theoretical frameworks that underly qualitative research), reflexivity and ethics, methods (e.g., developing interview guides, sampling, conducting interview and focus groups), analysis (e.g., transcription, thematic analysis, IPA, grounded theory, discourse analysis, content analysis), and evaluation and dissemination (e.g., validity, open science, writing and publishing, impact).