Quantitative Methods

Quantitative Methods

The Psychology Department has a strategic focus on training in advanced methodology, especially quantitative methods.  Advanced quantitative skills are increasingly important in conducting state-of-the–art research, and in post-doctoral and academic placements.  Recent and ongoing faculty searches have emphasized expertise in quantitative methods.  In addition to a standard two-semester sequence in statistics (PSY 507 and PSY 508), students may choose courses in topics such as multi-level modeling, test theory, structural equation modeling, computational modeling, and other topics.  A course in neuroscience methods (PSY 511) is offered annually.  Other resources for students seeking training in advanced methodology include courses in other departments (Statistics, Human Development and Family Studies, Educational Psychology, Information Sciences and Technology) and workshops on specific methodological topics. 

The Psychology Department has a faculty committee focused on quantitative methods in research and teacheing (see below), and it participates in the Consortium for the Advancement of Research Methods and Analysis (CARMA).

Quantitative Methods Faculty

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Quantitative Methods Labs

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Related Resources

Courses in Psychology

PSY 507 Analysis of Psychological Data I (annually in fall)
PSY 508 Analysis of Psychological Data II (Spring 2022)
PSY 509 Psychometrics (Spring 2022)
PSY 509 Introduction to Classical and Modern Test Theory (periodically)
PSY 509 Structural Equation Modeling (periodically)
PSY 509 Introduction to Exploratory Data Analysis and Data Management (periodically)
PSY 511 Neuroscience Methods (annually in spring)
PSY 531 Multilevel Theory, Measurement, and Analysis (annually, usually in spring)

PSY 535 Research Methods in I/O Psychology (Spring 2022)

Courses in Other Departments

EDPSY 507 Multiple regression

EDPSY 597 Structural Equation Modeling

HDFS 517 Multivariate Statistics
HDFS 523 Strategies for Data Analysis in Developmental Research
HDFS 526 Measurement
HDFS 530 Longitudinal SEM
HDFS 534 Person-specific Data Analysis
HDFS 597 Data Mining
HDFS 597 Latent Class Analysis (Introduction; Advanced)
HDFS 597 Hierarchical Linear Modeling
HDFS 597 Bayesian Statistics
HDFS 597 Person-Specific Ecological Momentary Assessment
HDFS 597 Advanced LISREL

SODA 501 Approaches and Issues in Big Data Social Science

SOC 580 Social Network Analysis

STAT 501 Regression
STAT 557 Data Mining I


The Department supports the use of SPSS, MPLUS, MATLAB, R, and Python.

Colloquia, Seminars, and Workshops