Advanced Item Response Theory (3 credits)
Advanced topics in item response theory, including multidimensional models, multilevel models, and mixture models.
Data Analysis Support (3 credits)
Statistical support for graduate students working on their dissertation and/or other research project(s).
Introduction to R (3 credits)
Data manipulation, visualization, and analysis in the R programming language. No prior programming experience is required.
Item Response Theory (3 credits)
Dichotomous, polytomous, and multidimensional IRT models. Parameter estimation methods. Model diagnostics, differential item functioning analysis, and linking and equating.
Quantitative Methods in Educational Research I (3 credits)
Techniques in data collection and data analysis used in educational and psychological research. Graphical and tabular representation of data. Concepts of statistical inference in educational contexts.
Test Security and Data Forensics (3 credits)
Traditional methods for detecting test fraud and recent developments in data forensics.