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Intermediate Regression with statsmodels in Python

4.4+
14 reviews
Intermediate

Learn to perform linear and logistic regression with multiple explanatory variables.

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4 Hours14 Videos52 Exercises
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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. In this course, you’ll build on the skills you gained in "Introduction to Regression in Python with statsmodels", as you learn about 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, discover how interactions between variables affect predictions, and understand how linear and logistic regression work.
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In the following Tracks

Statistics Fundamentals with Python

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  1. 1

    Parallel Slopes

    Free

    Extend your linear regression skills to parallel slopes regression, with one numeric and one categorical explanatory variable. This is the first step towards conquering multiple linear regression.

    Play Chapter Now
    Parallel slopes linear regression
    50 xp
    Fitting a parallel slopes linear regression
    100 xp
    Interpreting parallel slopes coefficients
    100 xp
    Visualizing each explanatory variable
    100 xp
    Visualizing parallel slopes
    100 xp
    Predicting parallel slopes
    50 xp
    Predicting with a parallel slopes model
    100 xp
    Visualizing parallel slopes model predictions
    100 xp
    Manually calculating predictions
    100 xp
    Assessing model performance
    50 xp
    Comparing coefficients of determination
    100 xp
    Comparing residual standard error
    100 xp
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GroupTraining 2 or more people?

Get your team access to the full DataCamp library, with centralized reporting, assignments, projects and more

In the following Tracks

Statistics Fundamentals with Python

Go To Track

Datasets

Ad conversionCustomer churnTaiwan real estateFish measurement dataeBay auctions

Collaborators

Collaborator's avatar
Richie Cotton
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Maggie Matsui
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Amy Peterson
Maarten Van den Broeck HeadshotMaarten Van den Broeck

Senior Content Developer at DataCamp

Maarten is an aquatic ecologist and teacher by training and a data scientist by profession. He is also a certified Power BI and Tableau data analyst. After his career as a PhD researcher at KU Leuven, he wished that he had discovered DataCamp sooner. He loves to combine education and data science to develop DataCamp courses. In his spare time, he runs a symphonic orchestra.
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*4.4
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  • Ildar K.
    7 months

    i hope that this course would help to furhter career, 10x!

  • Yannick D.
    about 1 year

    I like the process used by Datacamp to teach us each subject. The interface is really easy and effecient to use. Learning programming is fun.

  • Joanna K.
    over 1 year

    Easy to understand, good job :)

  • Aldo M.
    over 1 year

    Very good, useful

  • Yasser A.
    over 1 year

    It’s great. It need a cheat sheet please!! :)

"i hope that this course would help to furhter career, 10x!"

Ildar K.

"I like the process used by Datacamp to teach us each subject. The interface is really easy and effecient to use. Learning programming is fun."

Yannick D.

"Easy to understand, good job :)"

Joanna K.

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