Intermediate Regression in R

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

Two of the most widely used statistical models are linear regression and logistic regression. These models are the key to unlocking the secrets of data sets. This course builds on the skills acquired in "Introduction to Regression in R" and covers both logistic and linear regression with multiple explanation variables. Learn how variables interact with real-world data such as Taiwan house prices and customer churn modeling, among other topics. This course will show you how to combine multiple explanatory variables in a model, how they interact and how logistic regression and linear regression work.

Course Overview

Virtual Labs

International Faculty

Post Course Interactions

Hands-On Training,Instructor-Moderated Discussions

Skills You Will Gain

Prerequisites/Requirements

Introduction to Regression in R

What You Will Learn

By the end of this course, you’ll know how to include multiple explanatory variables in a model, understand how interactions between variables affect predictions, and understand how linear and logistic regression work

Learn to perform linear and logistic regression with multiple explanatory variables

Course Content

Expand all sections

Module 1: Parallel Slopes

Module 2: Interactions

Module 3: Multiple Linear Regression

Module 4: Multiple Logistic Regression

Course Instructors

Richie Cotton

Curriculum Architect at DataCamp

Richie is a Learning Solutions Architect at DataCamp. He has been using R since 2004, in the fields of proteomics, debt collection, and chemical health and safety. He has released almost 30 R package...