Introducing Probability and Statistics to Students Who Have Had Calculus: A Bayesian Approach with Computing

• Activity Number: 65
• Type: Topic Contributed
• Date/Time: Sunday, August 9, 2015 : 4:00 PM to 5:50 PM
• Sponsor: Section on Statistical Education
• Author(s): Joseph Chang*
• Companies: Yale University

Abstract

Over a decade ago I had an opportunity to create a new course to introduce the general area of probability, statistics, and data analysis to students with a background in calculus who may be interested in taking a single semester course in this area but not ready to commit to two or more courses. The course adopted a Bayesian approach intended to enable the students to create models and analyze data using Markov chain Monte Carlo (MCMC), with a solid understanding of what they are doing and how it works. Designing the course involved constructing a streamlined path starting from basic probability and Bayes' rule, through Markov chains and MCMC, to applications of the methodology to a number of examples including standard models as well as models typically considered advanced for a course at this level. R and elements of computing are introduced early and used throughout the course for calculations, simulations, illustrations of concepts, and analysis of data. Several aspects of the class will be discussed, including the role of computing, benefits of the approach, and challenges encountered.