Public Health 460 - TellingStories/DataStatModelVi

The aim of this course is to provide students with the skills necessary to tell interesting and useful stories in real-world encounters with data. Specifically, they will develop the statistical and programming expertise necessary to analyze datasets with complex relationships between variables. Students will gain hands-on experience summarizing, visualizing, modeling, and analyzing data. Students will learn how to build statistical models that can be used to describe and evaluate multidimensional relationships that exist in the real world. Specific methods covered will include linear, logistic, and Poisson regression. This course will introduce students to the R statistical computing language and by the end of the course will require substantial independent programming. To the extent possible, the course will draw on real datasets from biological and biomedical applications. This course is designed for students who are looking for a second course in applied statistics/biostatistics (e.g. beyond PUBHLTH 391B or STAT 240), or an accelerated introduction to statistics and modern statistical computing.

Open to sophomore, junior, and senior Public Health majors only. PUBHLTH 460 requisite Students who cannot self-enroll and wish to be placed on a waiting list for this course, please submit a request on https://tinyurl.com/PHWaitlist-Core
Enrollment in this class will open to non-Public Health Sciences majors on May 5, 2026.
If you have not taken an intro stats course at UMass but still want to enroll in this course, you are encouraged to petition the instructor for permission, especially if any of the following apply: (a) you have taken AP Stats in high school, (b) you have taken a college-level intro stats course just not one of the ones listed above, or (c) you are confident in your quantitative skills and your ability to succeed in a fast-paced, advanced introductory course.
It is strongly encouraged for students to have prior R programming experience before taking this class. For example, having taken in a previous semester PUBHLTH 345 (3 credits), having taken previously or being currently enrolled in BIOSTATS 530 (1 credit), or having taken another class that has a focus on intro R programming.