This page contains materials from Dr. B’s courses (basic/advanced/graduate statistics and structural equation modeling) and these materials provided with multiple formats (SPSS, Excel, R, VassarStats, JASP/Jamovi) for use by students in her courses and the interested graduate student or researcher. This information is formatted so that an individual may download the entire course for a template when assigned as a course prep.
Course description: Principles and methods of statistics used in psychology; understanding and interpreting psychological data. Typically covers descriptive statistics, hypothesis testing, z-tests, t-tests, ANOVA, correlation, regression, and chi-square analyses.
Course description: A review of introductory statistics and investigation of research methods in behavioral sciences that require multivariate statistical models. This course takes an applied orientation and emphasizes the use of statistical packages. Topics include: linear models, principal components analysis, discriminant analysis, multiple regression analysis, multiple regression with categorical variables, and multi-factor ANOVA.
Course description: Use of the Analysis of Variance (ANOVA) Models and Multivariate Analysis in the design and analysis of psychological experiments. Topics include correlation, regression, t-test, ANOVA (between, repeated, and mixed), mediation, moderation, and exploratory factor analysis.
Course description: This course will cover an in depth exploration of structural equation modeling. You will learn the basic concepts of SEM and how to model different types of research questions, as well as how to report these models in APA style. Path analysis, confirmatory factor analysis, and multi-group models will be several types of techniques covered.