The Program offers three signature courses: Regression Modeling Strategies, Foundations of Statistical Inference, and Statistical Collaboration in Health Sciences.
- Regression Modeling Strategies. This course is taught in the spring by Professor Harrell, a leading expert in regression modeling strategies and author of the definitive textbook on the subject.
- Foundations of Statistical Inference. This course is taught every other year in the spring by Professor Blume, a leading expert in the foundations of statistical inference and likelihood methods for measuring statistical evidence.
- Statistical Collaboration in Health Sciences. This year long course sequence places a heavy emphasis on communication, teamwork, and interdisciplinary collaboration. Students role-play with real investigators and confront real-life problems such as opaque scientific direction, poor scientific formulation, lack of time, and ill-formulated data. The importance of understanding the underlying science behind collaborations is emphasized.
The signature courses emphasize and develop the core principles of our statistical curriculum, which are reinforced throughout the individual biostatistics curricula. For example, every course demonstrates and discusses Bayesian, Likelihood and Frequentist inferential approaches in the context of course topics. As well, demonstration and discussion of different regression modeling strategies is discussed in the context of applications that arise in course examples. Students are exposed to these concepts in their first-year course sequence when they are acquiring the necessary statistical skills for the signature courses.
The incorporation of contemporary topics, critical thinking skills, and intellectual flexibility encouraged in Regression Modeling Strategies and Foundations of Statistical Inference helps students form the basis of a modern view of statistical methods that is neither dogmatic nor rigid. Graduate programs have traditionally created a single course that addresses these topics. However, a disjointed treatment often leaves students on their own to discover and untangle opaque theoretical discussions that have remained controversial for nearly a century. Our students are encouraged to form and discuss their own viewpoints on these subjects in a succinct and accurate manner.