Hi everyone
Instats is excited to offer a free seminar, Introduction to Bayesian Modelling using RStan, on April 14th, led by Professor Justin Slater from the Department of Mathematics and Statistics at the University of Guelph. When tackling challenging statistical problems, understanding the data-generating process is essential, yet many researchers without advanced training struggle to know where to begin. This seminar fills that critical gap by introducing Bayesian statistics as a flexible, intuitive framework for building custom models tailored to your research context. You’ll explore key topics such as the fundamentals of Bayesian inference, the roles of prior and posterior distributions, and the basics of Markov Chain Monte Carlo (MCMC) methods as implemented in Stan. Through hands-on demonstrations, you’ll learn to express a simple custom statistical model in mathematical notation, convert it to Stan code, sample from its posterior distribution using MCMC, and diagnose common sampling issues. The workshop also includes applications to simple problems in biostatistics and epidemiology, providing you with a solid foundation to continue developing autonomous and rigorous data analytic practices.
Sign up today to secure your spot, and feel free to share this opportunity with colleagues and students who might benefit!
Best wishes
Michael Zyphur
Professor and Director
Institute for Statistical and Data Science
instats.org
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Michael Zyphur
Professor
UQ Business School
University of Queensland
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