Linear Regression, GLMs and GAMs with R

How to extend linear regression to specify and estimate generalized linear models and additive models.
4.34 (255 reviews)
Udemy
platform
English
language
Data Science
category
Geoffrey Hubona, Ph.D.
instructor
Linear Regression, GLMs and GAMs with R
2,424
students
8 hours
content
Sep 2020
last update
$44.99
regular price

What you will learn

Understand the assumptions of ordinary least squares (OLS) linear regression.

Specify, estimate and interpret linear (regression) models using R.

Understand how the assumptions of OLS regression are modified (relaxed) in order to specify, estimate and interpret generalized linear models (GLMs).

Specify, estimate and interpret GLMs using R.

Understand the mechanics and limitations of specifying, estimating and interpreting generalized additive models (GAMs).

Screenshots

Linear Regression, GLMs and GAMs with R - Screenshot_01Linear Regression, GLMs and GAMs with R - Screenshot_02Linear Regression, GLMs and GAMs with R - Screenshot_03Linear Regression, GLMs and GAMs with R - Screenshot_04
Related Topics
701416
udemy ID
12/19/2015
course created date
11/22/2019
course indexed date
Bot
course submited by
Linear Regression, GLMs and GAMs with R - | Comidoc