(3 Lec, 1 2-hr Lab) Survey of standard methods and related conceptual issues employed in psychological research. Both experimental and non-experimental methods will be reviewed. Pre: 100.
Psychology as applied to education, including major theories and research and development, cognitive, sociocultural, and multicultural approaches to teaching and learning. Incorporates introductions to standardized testing, classroom assessment, motivation, instructional planning and classroom management. (Cross-listed as EDEP 311)
Introduction to quantitative methods in behavioral sciences and the general linear model with a focus on regression. Topics include correlation, bivariate and multiple regression, mediation, and moderation. Requires basic statistics. (Meets PhD common inquiry methods requirement or elective.)
Theories and applications to latent variables models. Topics include path analysis, exploratory and confirmatory factor analysis, structural equation models (SEM), multi-sample SEM, mean structure, latent growth curve models, and multilevel SEM. Requires basic knowledge of regression.
Analysis of multiple dependent variables. Topics include multivariate normal distribution, Hotelling’s 72, multivariate analysis of variance (MANOVA), discriminant analysis, cluster analysis, canonical correlation, and principal components analysis (PCA). Pre: 610, EDEP 604, or consent.
Theories and applications of modern psychometrics. Topics include unidimensional and multidimensional models of item response theory, detecting biased items, measurement invariance, scaling methods, and current issues in psychometrics. Pre: 616, EDEP 616, or consent.
Theories and methods for data analysis with categorical and discrete variables. Topics include contingency tables; logistic regression; log-linear models; and introduction to generalized linear models. Pre: 610, EDEP 604, or consent. (Cross-listed as EDEP 618)
Theories and applications of analysis of nested (clustered) data. Topics include fixed and random effects, intra-class correlation, cross-sectional multilevel models, and multilevel models, and multilevel models with repeated measures and longitudinal data. Requires basic knowledge of regression.
Specific and newly emerging topics in statistics, including casual inference, analysis of missing data, and statistical machine learning. Content varies and focuses on advanced topics not covered in other PSY methods and statistics courses. Repeatable two times. PSY majors only. A-F only. Pre: 610 (with a minimum grade of B) or instructor consent.