So, over the summer I took it upon myself to teach a class on Bayesian Data Analysis, based on the following text,
This was a class put together for several coworkers, including members of our research team at Tableau. Here is a blurb summarizing course content:
Tableau provides various statistical methods, including primitives like Trend Lines (Regression). Our native solutions tend to use rely on Null Hypothesis Significance Testing, which are related to p-values, and a frequentist interpretation of probability. However, Bayesian Statistics is an alternative approach, that has been slowly been gaining traction in several fields.
This class introduced the technical details of Bayesian statistics. It ran July 19 – Sept 27, 2016 and used Doing Bayesian Data Analysis, Second Edition.
- Weeks 1-3 will motivates the Bayesian approach to statistics.
- Weeks 4-7 will give you tools to implement Bayes in R.
- Weeks 8-10 will show how to use Bayesian alternatives to t-tests, regression, and ANOVA.
It was a great experience!
|1||Ch2: Intro to Bayesian Reasoning||July 19||Yes|
|2||Ch4: Intro to Probability Theory||July 26||Yes|
|3||Ch5: Intro to Bayes Theorem||Aug 2||No|
|4||Ch7: Markov Chain Monte Carlo (MCMC)||Aug 9||Yes|
|5||Ch9: Hierarchical Models||Aug 23||Yes|
|6||Ch11: Bayesianism vs Frequentism||Aug 30||No|
|7||Ch16: Bayesian t-test||Sept 6||No|
|8||Ch17: Bayesian linear regression||Sept 20||Yes|
|9||Ch19: Bayesian 1-way ANOVA||Sept 27||Yes|
Your mileage may vary with the slides, of course. They work best in presentation mode – otherwise some of the transitions are a bit jumpy. I constructed these by myself, with lots of help from our textbook.