Quantitative Psychology Minor Courses
This page is a work in progress and subject to change.
If a course you wish to take is not listed here, please see the instructions for the Psychology Department's Quantitative Minor about how to add courses. For other questions, please contact Brian Flaherty.
Applied Math
- AMATH 352 Applied linear algebra and numerical analysis
Biostatistics
- BIOST 544 Introduction to Biomedical Data Science
Computer Science
- CSE 416 Introduction to machine learning
- CSE 546 Machine learning
Center for Statistics and Social Sciences
- CS&SS 504 Applied regression
- CS&SS 509 Introduction to mathematical statistics: Econometrics
- CS&SS 510 Maximum likelihood methods for the social sciences
- CS&SS 512 Time series and panel data
- CS&SS 526 Structural equation models for the social sciences
- CS&SS 536 Analysis of categorical and count data
- CS&SS 560 Hierarchical sodeling for the social sciences
- CS&SS 564 Bayesian statistics for the social sciences
- CS&SS 566 Causal modeling
- CS&SS 567 Statistical analysis of social networks
- CS&SS 569 Visualizing data
- CS&SS 589 Multivariate data analysis for the social sciences
Educational Psychology
- EDPSY 559 Validity Theory
- EDPSY 575 Structural Equation Modeling I
- EDPSY 576 Multilevel Modeling
- EDPSY 588 Structural Equation Modeling II
Neuroscience
- NEURO 545 Quantitative Methods In Neuroscience
Psychology
- PSYCH 481 Seminar in advanced quantitative methods
- PSYCH 509 Core concepts in computational modeling
- PSYCH 530 Introduction to Manifest Path, Confirmatory Factor, and Latent Variable Path Analysis for Psychology
- PSYCLN 510 (was PSYCH 531) Research methods in clinical & community psychology
- PSYCH 548 Advances in quantitative psychology - Hierarchical linear models
Statistics
- STAT 416 Introduction to machine learning
- STAT 512 Statistical inference
- STAT 513 Statistical inference
- STAT 527 Nonparametric regression and classification
- STAT 535 Introduction to machine learning