Biostatistics 560 - Stat Modeling/Health Data Sci

The aim of this course is to provide students with the modeling skills necessary to analyze, interpret and report on complex relationships between variables in real world data using descriptive, predictive and causal inference frameworks. With linear and logistic regression as the primary tools, students will develop the expertise to identify analytic goals, execute statistical programming necessary to build statistical models and report findings in a reproducible computing environment. To the extent possible, the course will draw on real datasets from a variety of public health settings. Students will work with the R statistical computing language for model fitting and analyses.

BIOSTATS 560 req Prior programming experience with R or concurrent enrollment in BIOSTATS 530 (Introduction to Statistical Computing) with R is required.
If you haven't taken an introductory UMass (bio)statistics course, you will need instructor permission to enroll. Permission may be granted if you took AP Statistics, completed another college-level stats course, or feel confident in your quantitative skills.

This course is offered in person on the Amherst campus. A synchronous Zoom option may be available for all or selected class meetings; please check with the instructor for details.