Associate Professor Sama Low-Choy
An cookies-and-candy introduction to Bayesian thinking: a new ending to the boardbook "Bayesian Probability for Babies" by Chris Ferrie
You may have wondered: what is all the fuss, about Bayesian statistics? If so, please come to this reading of "Bayesian probability for Babies", together with my own ending, for researchers. In his book, astrophysicist Chris Ferrie tells a story about cookies, and the chance of a bite with no candy on it. In fact, this is a clever, visual metaphor for the Bayesian concepts of data, and the probability of hypotheses given the data observed. Here, I continue the metaphor, in a slightly different vein, to highlight the points of difference and similarity between Bayesian thinking and classical statistical thinking. In this workshop, you will work through the rich landscape of cookies and candy (as well as other visual landscapes) to explore the simple arithmetic (plus, minus, times, divide) involved. Along the way I will point out philosophical nuances of Bayesian probabilities, and how these may help support research.
In so doing, I guide you through Bayesian ideas that disrupt assumptions embedded within the classical statistical framework. At the same time, we disrupt the traditional pedagogic approach to teaching statistical thinking that typically relies on mathematics. Utilizing Chris's approach, we deviate from the using "Introductions" to Bayesian statistics which are typically couched in terms of integrals. Ferrie's boardbook for babies (and their parents) presents a much simpler way to introduce Bayes theorem. There are no integral signs! My extra material could be described as taking the next steps, i.e. "Bayesian probability for toddlers".