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The Statistics, Measurement, and Evaluation in Education program provides multiple courses in applied statistics, ranging from fundamental quantitative research principles to sophisticated techniques like multivariate analysis, hierarchical linear modeling, and structural equation modeling. Our curriculum includes diverse educational measurement courses addressing classical test theory, modern psychometric approaches, and reliability analysis frameworks. Students can explore an extensive selection of advanced statistical and quantitative methodology courses, encompassing probability theory, survey sampling techniques, discrete data analysis, stochastic processes, longitudinal data methods, probabilistic inference, and other innovative quantitative approaches. The program instructs students in various statistical computing platforms such as SPSS, SAS, R, Mplus, Amos, HLM, and BILOG-MG. Additionally, students complete coursework in cognitive learning principles, developmental psychology components, and assessment methodology.