Course
Generalized Linear Models in R
IntermediateSkill Level
Updated 08/2024RProbability & Statistics4 hr14 videos51 Exercises4,050 XP21,545Statement of Accomplishment
Create Your Free Account
or
By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.Loved by learners at thousands of companies
Training 2 or more people?
Try DataCamp for BusinessCourse Description
Prerequisites
Intermediate Regression in R1
GLMs, an extension of your regression toolbox
This chapter teaches you how generalized linear models are an extension of other models in your data science toolbox. The chapter also uses Poisson regression to introduce generalize linear models.
2
Logistic Regression
This chapter covers running a logistic regression and examining the model outputs.
3
Interpreting and visualizing GLMs
This chapter teaches you about interpreting GLM coefficients and plotting GLMs using ggplot2.
4
Multiple regression with GLMs
In this chapter, you will learn how to do multiple regression with GLMs in R.
Generalized Linear Models in R
Course Complete
Earn Statement of Accomplishment
Add this credential to your LinkedIn profile, resume, or CVShare it on social media and in your performance reviewEnroll Now
FAQs
What makes this course advanced compared to a standard regression course in R?
It goes beyond ordinary linear regression to cover generalized linear models, including logistic regression for binary outcomes and Poisson regression for count data.
Which specific GLM families are taught in this course?
You will learn Poisson regression for modeling count data and logistic regression for binary outcomes, along with how to interpret and visualize the results using ggplot2.
Do I need to have completed an intermediate regression course first?
Yes. The prerequisites include Intermediate Regression in R, along with dplyr, ggplot2, and introductory statistics, so solid regression foundations are expected.
What kinds of real-world problems can I solve with GLMs?
GLMs let you model outcomes that standard linear regression cannot, such as predicting whether a customer churns (binary) or how many support tickets arrive per day (count).
How are the GLM results visualized in this course?
You will use ggplot2 to create plots that help interpret model coefficients, predicted probabilities, and count predictions, making complex results easier to communicate.
Join over 19 million learners and start Generalized Linear Models in R today!
Create Your Free Account
or
By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.Grow your data skills with DataCamp for Mobile
Make progress on the go with our mobile courses and daily 5-minute coding challenges.