Please join our monthly Biomedical Data Science Grand Rounds with Nicholas Horton, ScD, Professor of Statistics and Data Science, Amherst College on Thursday, October 15 at 12:00pm via Zoom!

Talk title: "Multivariate thinking and the introductory biostatistics and data science course: Preparing students to make sense of a world of observational data”

Location: Zoom (no registration required) 

Webinar URL: 

https://dartmouth.zoom.us/j/99671590847?pwd=YzJxQzIwT084V1BEQ0RZVFJsdjIwUT09

Meeting ID: 996 7159 0847

Password: 033627

Host: Tor Tosteson, ScD

Talk Summary 

We live in a world of ever expanding "found" (or observational) data. To make decisions and disentangle complex relationships, students need a solid background in design and confounding. The revised Guidelines for Assessment and Instruction in Statistical Education (GAISE) College Report enunciated the importance of multivariate thinking as a way to move beyond bivariate thinking. But how do such learning outcomes compete with other aspects of statistics knowledge (e.g., inference and p-values) in introductory courses that are already overfull? In this talk, I will offer some reflections and guidance about how we might move forward, with specific implications for introductory biostatistics and data science courses.

Biography

Dr. Nicholas Horton is an applied biostatistician with research interests in missing data and longitudinal regression models.  He is passionate about improving quantitative and computational literacy for students with a variety of backgrounds. Dr. Horton is a Fellow of the American Statistical Association and the American Association for the Advancement of Science and is co-chair of the National Academies Committee on Applied and Theoretical Statistics (CATS). He was a member of the Academies consensus report on "Data Science for Undergraduates" and the Guidelines for Assessment and Instruction in Statistics Education revised College report.  Dr. Horton chaired the Committee of Presidents of Statistical Societies and the American Statistical Association working group that revised guidelines for undergraduate programs in statistics.