A/B testing in R

Key Takeaways:
  • Learn how to analyze A/B test datasets.
  • Learn how to measure the performance of an A/B test and make decisions from the results.
  • Learn about sampling and randomization techniques to avoid bias in your data experiments.
Tuesday, February 14, 11 am ET

Register for the webinar


A/B testing is a type of data experiment. It is an important tool for product and marketing teams for comparing two versions of features or content to see which is best. This live training provides an introduction to A/B testing in R, showing how you can compare the performance of two groups and determine whether or not your data experiment is a success.

We will be using DataCamp Workspace. All you need is a DataCamp account. If you need help, read the Getting Started with Workspace tutorial. Note that members of some enterprise groups do not yet have access to use DataCamp Workspace. Create a free DataCamp account with your personal email address to follow along.

We recommend that you have taken the following course before attending:

  • Intermediate R

Related cheat sheet:

Presenter Bio

Arne Warnke Headshot
Arne WarnkeHead of Emerging Curriculum at DataCamp

Arne is a trained mathematician with a PhD in economics and applied statistics who worked with causal inference as well as randomized experiments both in research and consulting. At DataCamp, he is responsible for data engineering and machine learning engineering content. Before joining DataCamp, Arne worked for several years as a data scientist.