A Biostatistical Literacy Course: Teaching Medical and Public Health Professionals to Read and Interpret Statistics in the Published Literature

Abstract

We present a unique and innovative course, Biostatistical Literacy, developed at the University of Minnesota. The course is aimed at public health graduate students and health sciences professionals. Its goal is to develop students’ ability to read and interpret statistical results in the medical and public health literature. The content spans the typical first-semester introductory material, including data summaries, hypothesis tests and interval estimation, and simple linear regression, as well as material typically presented in a second introductory course, including multiple linear regression, logistic regression, and time-to-event methods. The focus is on when to use a method and how to interpret the results; no statistical software computing is taught. A flipped classroom approach is used, where students are first exposed to the material outside of class, and class time is devoted to actively exploring and applying the concepts in greater depth. The course structure, the class activities, and feedback from students will be shared. Supplementary materials for this article are available online.

Keywords:

• Active learning
• Flipped classroom
• Introductory biostatistics
• Statistical literacy

Supplementary Materials

The supplementary materials include Figure 2: Mean end-of-semester assessment scores, 2014–2019 academic years, Sample Unit Materials Part A: Learning Objectives, Sample Unit Materials Part B: Concept Activity, and Sample Unit Materials Part C: Literature Activity.

Acknowledgments

For their help in refining and improving the course, we would like to thank the other Biostatistical Literacy course instructors, Mark Fiecas, Ph.D., and Marta Shore, M.S., as well as the many graduate student teaching assistants who have assisted in the active learning classroom. We owe a huge debt of gratitude to Susan Telke, M.S., long-time biostatistics instructor, who worked with Ann to understand the need and secure the initial support for developing a biostatistical literacy course. Finally, we are forever grateful to the School of Public Health’s Office of E-Learning Services, and particularly to Jim Harpole, Kris Woll, Katy Korchik, Sara Hurley, Ph.D., and Ellyn Buchanan, Ph.D., for their excellent support of both online and hybrid courses.