Bayesian Regression Modeling with rstanarm

via

DataCamp

Course Features

Duration

4 hours

Delivery Method

Online

Available on

Limited Access

Accessibility

Mobile, Desktop, Laptop

Language

English

Subtitles

English

Level

Intermediate

Teaching Type

Self Paced

Video Content

4 hours

Course Description

Bayesian estimation can be used to model techniques that are dependent on p values. This course will show you how to calculate linear regression models using Bayesian methods and the rstanarm. You will also learn about posterior predictive model checking, prior distributions, and how to use the Bayesian framework. The model you have constructed will be used for predicting new data.

Course Overview

Virtual Labs

International Faculty

Post Course Interactions

Hands-On Training,Instructor-Moderated Discussions

Skills You Will Gain

Prerequisites/Requirements

Intermediate Regression in R

Introduction to Data Visualization with ggplot2

Bayesian Modeling with RJAGS

What You Will Learn

In this course, you’ll learn how to estimate linear regression models using Bayesian methods and the rstanarm package

Learn how to leverage Bayesian estimation methods to make better inferences about linear regression models

You’ll also learn how to use your estimated model to make predictions for new data

You’ll be introduced to prior distributions, posterior predictive model checking, and model comparisons within the Bayesian framework

Course Content

Expand all sections

Module 1: Introduction to Bayesian Linear Models

Module 2: Modifying a Bayesian Model

Module 3: Assessing Model Fit

Module 4: Presenting and Using a Bayesian Regression

Course Instructors

Jake Thompson

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 educat...