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Intermediate Regression in R

Intermediate
4.4+
24 reviews
Updated 04/2025
Learn to perform linear and logistic regression with multiple explanatory variables.
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RProbability & Statistics4 hours14 videos50 Exercises4,150 XP29,131Statement of Accomplishment

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Course Description

Linear regression and logistic regression are the two most widely used statistical models and act like master keys, unlocking the secrets hidden in datasets. This course builds on the skills you gained in "Introduction to Regression in R", covering linear and logistic regression with multiple explanatory variables. Through hands-on exercises, you’ll explore the relationships between variables in real-world datasets, Taiwan house prices and customer churn modeling, and more. 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.

Prerequisites

Introduction to Regression in R
1

Parallel Slopes

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2

Interactions

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3

Multiple Linear Regression

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4

Multiple Logistic Regression

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Intermediate Regression in R
Course
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*4.4
from 24 reviews
63%
21%
13%
4%
0%
  • Andrew V.
    about 1 month

    Great

  • Dan L.
    8 months

    I had 1 thin in mind about lm(or glm) function: for complex interactions such as "lm(mass_g ~ length_cm * height_cm * species *0, data = fish) " for eample, how can I manully calculate the predictions or get a function ( exact or aproximation ) for the predictions?

  • Vern V.
    12 months

    Like most of the Datacamp short courses, this one is concise and clear. The course covers a lot of ground on Linear and Logistic Regression, but if one has some background then one learns how to get it done with R.

  • Héctor P.
    about 1 year

    "The course is very interesting. The instructor develops the topics very well and the exercises are very challenging."

  • Li D.
    over 1 year

    Great course for beginners

"Great"

Andrew V.

"I had 1 thin in mind about lm(or glm) function: for complex interactions such as "lm(mass_g ~ length_cm * height_cm * species *0, data = fish) " for eample, how can I manully calculate the predictions or get a function ( exact or aproximation ) for the predictions?"

Dan L.

"Like most of the Datacamp short courses, this one is concise and clear. The course covers a lot of ground on Linear and Logistic Regression, but if one has some background then one learns how to get it done with R."

Vern V.

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