Skip to main content
HomeRA/B Testing in R

A/B Testing in R

Learn the basics of A/B testing in R, including how to design experiments, analyze data, predict outcomes, and present results through visualizations.

Start Course for Free
4 Hours16 Videos54 Exercises

Create Your Free Account

GoogleLinkedInFacebook

or

By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.
GroupTraining 2 or more people?Try DataCamp For Business

Loved by learners at thousands of companies


Course Description

A/B testing is a common experimental design for human behavior research in industry and academia. A/B tests compare two variants to determine if the measurement shows different performance and if measurements vary in a meaningful way. By learning about A/B testing and presenting the results, you can make data-driven decisions and predictions.

Build an Understanding of A/B Design



In this course, you’ll learn what questions the A/B tests can address, the important considerations to be aware of in A/B tests, how to answer the questions at hand, and how to visualize the data. You’ll also learn how to determine the sample size needed in an experiment, conduct analyses appropriate for the data and hypothesis at hand, determine if the results can be regarded with confidence, and present the results to an audience regardless of statistical background.

Learn How to Analyze A/B Test Data



This course covers parametric and non-parametric A/B tests, such as t-tests, Mann-Whitney U test, Chi-Square test of independence, Fisher’s exact test, and Pearson and Spearman correlations. Additionally, you’ll explore a power analysis for each test.

Predict Outcomes Based on Data



As you progress, you’ll also learn to run linear and logistic regressions to predict outcomes based on data and previous findings.

Present Results to Any Audience with Visualizations



By the time you complete this course, you’ll have a thorough understanding of A/B tests, the analyses you can perform with them, and how to relay the results with data visualizations.
For Business

GroupTraining 2 or more people?

Get your team access to the full DataCamp library, with centralized reporting, assignments, projects and more
Try DataCamp for BusinessFor a bespoke solution book a demo.
  1. 1

    Introduction to A/B Tests

    Free

    Gain an understanding of A/B tests and design. Learn about the aspects to be aware of to ensure appropriate handling of the data and analyses.

    Play Chapter Now
    A/B testing and design
    50 xp
    A/B subject design
    50 xp
    Format and histograms
    100 xp
    Considerations in A/B testing
    50 xp
    Type I error in A/B tests
    50 xp
    Sampling
    100 xp
    Family-wise error rate
    100 xp
    Power and sample size
    50 xp
    Power impacts
    100 xp
    Determine the ideal sample size
    100 xp
    Regression to the mean
    100 xp
For Business

GroupTraining 2 or more people?

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

Datasets

absentcovidwebdatagamedataSiteSales

Collaborators

Collaborator's avatar
Jasmin Ludolf
Collaborator's avatar
Maham Khan
Collaborator's avatar
James Chapman
Lauryn Burleigh HeadshotLauryn Burleigh

Cognitive Neuroscientist

Lauryn has PhD in Cognitive Neuroscience from LSU. They are interested in using analyses to make data driven decisions and making data and statistics accessible. Currently, they are applying for data science and user experience research positions.
See More

What do other learners have to say?

Join over 14 million learners and start A/B Testing in R today!

Create Your Free Account

GoogleLinkedInFacebook

or

By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.