The objective is to introduce Bayesian methodology for public health applications, with an emphasis on computational solutions for addressing scientific questions in public health.

Years offered:

• 4th quarter, 2019
• 4th quarter, 2021

Textbooks and Reading

• Peter D. Hoff, A First Course in Bayesian Statistical Methods, 2009

Hoff’s website

Github

members only

Grading and Exams

• Weekly homework assignments and a data analysis project

Prerequisites

We will assume that students have completed the 140.650 series of applied biostatistics courses (or equivalent) offered by the Department of Biostatistics in the Johns Hopkins Bloomberg School of Health. This course uses some linear algebra and calculus. We support and provide examples for computing with R, JAGS, and stan.