Applied Bayesian Statistics for Education Research
Covers the basic elements of Bayesian statistics through lecture, discussion and practice. Focuses on why the Bayesian perspective provides a powerful alternative to the frequentist perspective. Topics to be covered include; Bayes' theorem, Markov chain Monte Carlo sampling and the "rjags" program, Bayesian hypothesis testing, Bayesian model building and evaluation, Bayesian approaches to missing data, Bayesian model averaging, Bayesian multilevel models and latent variable models, and philosophical debates within the Bayesian paradigm of statistics.
Summary
Recent recorded grades — Fall 2023: 4.00 GPA, 100.0% A/AB (n=11 letter grades); Fall 2024: 4.00 GPA, 100.0% A/AB (n=12 letter grades); Fall 2025: 4.00 GPA, 100.0% A/AB (n=18 letter grades).
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