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DataCamp

A/B Testing in R

via DataCamp

Overview

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

A/B testing is a common experimental design for human behavior research in industry and academia. 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.

Syllabus

  • Introduction to A/B Tests
    • 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.
  • Comparing Groups
    • Learn common analyses to compare A/B groups. Understand the appropriate approach to each test given their assumptions and limitations.
  • Associations of Variables
    • Learn to analyze the trend and relationship of variables in A/B groups. Understand how to assess and present the results to any audience.
  • Regression and Prediction
    • Understand the basis of regression and regression lines. Learn to run regressions, predict data based on the regression model, and visually present the results.

Taught by

Lauryn Burleigh

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