Bayesian Statistics for Data Science

What is Bayesian Statistics, and how can it be used for my data science problems? Ryan Chitwood will give an introduction to Bayesian inference and its application. We'll discuss constructing prior distributions, quantifying uncertainty, and interpreting results, highlighting the advantages of the Bayesian approach. We'll introduce the statistical modeling platform, Stan, as a tool for doing Bayesian statistics. Finally, we'll look at some examples of where Bayesian methods are being used in data science today. If you've ever been disappointed by a p-value, don't miss this talk!

Ryan is an early-career data scientist with a background in quantitative ecology and wildlife biology. He has been speaking, teaching, and writing about statistics and data science for half a decade. Ryan is part data geek, part bird nerd, and has recently made data science his career priority. He holds a BS in Ecology and a MS in Wildlife Science from the University of Georgia. Ryan likes programming in R and strongly believes that you should always plot the data! When he's not working on data science-y things, you can probably find him out bird watching or trying out a new recipe at home.

• Important to know
We normally use the first 30 min to socialize a bit and will start the presentation promptly at 6pm. Please RSVP with your first and last name so we can get security clearance. Guests are also required to RSVP.