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Introduction to Linear Regression Analysis, May 20-23
Dive into the essentials of regression analysis, learning to navigate and interpret social science data with confidence.
Social Network Analysis with Human Subjects, May 20-23
Engage in hands-on sessions that cover the entire research process—from formulating research questions and ethical considerations to data collection, analysis, and interpretation of results.
Meta-Analysis and Systematic Review, May 20-24
Learn how to calculate various kinds of effect sizes and to use them to conduct and make appropriate inferences from meta-analyses.
Modern Causal Inference: Experiments, Matching, and Beyond, May 20-24
Learn and actively work with exact matching, propensity score matching, fixed effects panel designs, difference-in-differences, synthetic control, instrumental variables, and regression discontinuity designs.
Multilevel Analysis with R, May 20-24
Set up and manage multilevel data, identify data structures, choose the appropriate model specification, evaluate fixed and random effects, interpret and visualize statistical results.
Navigating Text: An Introduction to Natural Language Processing and Text Mining in R, May 22-24
Course topics include principles and techniques of text analysis in R. Natural Language Processing (NLP) extracts insights from large amounts of natural language. Lessons will help students add NLP techniques to their research, business and data science toolset.
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