  Physics increasingly relies on Bayesian techniques for rigorous data analysis
and model-to-data comparison. This paper describes how these methods can be
implemented to answer questions of relevance to the teaching of introductory
physics concepts. It demonstrates the proper application of statistical
approaches to quantitatively assess when more complex calculations are
necessitated by data. The case study of a simple pendulum allows for the
incorporation of the precision commonly found in introductory physics
laboratories in order to rigorously assess model preference between the small
angle and exact expressions for the period. This extends the current simple
pendulum literature's focus on individual assessments of different
approximations to the exact solution to place such discussions on a data-driven
foundation and provides guidance to instructors for teaching laboratory design.
