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appliedstatisticalprogramming2022

Problem set repository for Applied Statistical Programming (WUSTL 2022)

bayesian_summer_study

PURPOSE: “This course teaches data analysis, but it focuses on scientific models first. The unfortunate truth about data is that nothing much can be done with it, until we say what caused it. We will prioritize conceptual, causal models and precise questions about those models. We will use Bayesian data analysis to connect scientific models to evidence. And we will learn powerful computational tools for coping with high-dimension, imperfect data of the kind that biologists and social scientists face.”

hello-world

I practice my github skills once again!

human-rights-latent-variable

R code and STAN model files that generate latent human rights scores using a dynamic ordinal item-response theory model.

idealstan

idealstan offers item-response theory (IRT) ideal-point estimation for binary, ordinal, counts and continuous responses with time-varying and missing-data inference. Latent space model also included. Full and approximate Bayesian sampling with 'Stan' (www.mc-stan.org).

ps5024_poster

ps_5024_causal_exam_prep

Ideal answers for problem set problems

python_summer2022

WashU 2022 Python Summer Course