Multiple and Logistic 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

This course will improve your linear regression skills. Multiple and logistic regression techniques will be taught to help you predict numeric and categorical outcomes using multiple input variables. These models can also be fitted, visualized and interpreted. Next, you'll use your skills and knowledge to discover more about Italian restaurants around New York City.

Course Overview

Virtual Labs

International Faculty

Case Based Learning

Post Course Interactions

Case Studies,Hands-On Training,Instructor-Moderated Discussions

Skills You Will Gain

Prerequisites/Requirements

Correlation and Regression in R

What You Will Learn

In this course you'll take your skills with simple linear regression to the next level

You will gain the skills to model and predict both numeric and categorical outcomes using multiple input variables

You'll also learn how to fit, visualize, and interpret these models

Course Content

Expand all sections

Module 1: Parallel Slopes

Module 2: Evaluating and extending parallel slopes model

Module 3: Multiple Regression

Module 4: Logistic Regression

Course Instructors

Ben Baumer

Assistant Professor at Smith College

Ben is an Assistant Professor in the Statistical Data Sciences Program at Smith College. He completed his Ph.D. in Mathematics at the Graduate Center of the City University of New York in 2012. He is...