How to (Not) Lie with Statistics

(3 Credit Hours) · Undergraduate

Are stay-at-home orders effective during a pandemic? Should parents allow kids to have screen time? What role did demographic shifts play in the 2020 elections? Does the infield shift work? Modern society constantly faces questions that require data, statistics, and other empirical evidence to answer well. But the proliferation of niche media outlets, the rise of fake news, and the increase in academic research retraction makes navigating potential answers to these questions difficult. This course is designed to give students tools to confront this challenge by developing their statistical and information literacy skills. It will demonstrate how data and statistical analyses are susceptible to a wide variety of known and implicit biases, which may ultimately lead consumers of information to make problematic choices. The course will consider this issue from the perspectives of consumers of research as well as researchers themselves. We will discuss effective strategies for reading and interpreting quantitative research while considering the incentives researchers face in producing it. Ultimately, students will complete the class better equipped to evaluate empirical claims made by news outlets, social media, instructors, and their peers. The goal is to encourage students to approach data-driven answers to important questions with appropriate tools rather than blind acceptance or excessive skepticism.