Course Bayesian Regression Modeling with rstanarm
Learn how to leverage Bayesian estimation methods to make better inferences about linear regression models.
This online course about Bayesian Regression Modeling with rstanarm covers a key part of what a future data analyst would require.
Bayesian estimation offers a flexible alternative to modeling techniques where the inferences depend on p-values. In this course, you’ll learn how to estimate linear regression models using Bayesian methods and the rstanarm package. You’ll be introduced to prior distributions, posterior predictive model checking, and model comparisons within the Bayesian framework. You’ll also learn how to use your estimated model to make predictions for new data.
Enroll now in this Bayesian Regression Modeling with rstanarm course, and don’t miss the opportunity of learning with the best, as Jake Thompson is. With 45 enriching exercises, 15 videos, and an estimated time of 4 hours to successfully end up the course, you will become one of the best.
Psychometrician, ATLAS, University of Kansas
Jake is a Psychometrician at the Center for Accessible Teaching, Learning, and Assessment Systems (ATLAS) and received his PhD in Educational Psychology and Research. His interests are include educational assessment, diagnostic classification modeling, and Bayesian inference. Follow him at @wjakethompson on Twitter or on his blog.