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A/B Testing in R

Intermediate
4.7+
18 reviews
Updated 05/2025
Learn the basics of A/B testing in R, including how to design experiments, analyze data, predict outcomes, and present results through visualizations.
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RProbability & Statistics4 hours16 videos54 Exercises4,400 XP2,336Statement of Accomplishment

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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.

Prerequisites

Hypothesis Testing in R
1

Introduction to A/B Tests

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2

Comparing Groups

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3

Associations of Variables

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4

Regression and Prediction

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A/B Testing in R
Course
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*4.7
from 18 reviews
72%
28%
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  • Oleksandr
    2 days

  • Abu
    4 days

    This was awesome

  • Abdullah
    5 days

  • Bennett
    11 days

    This was the best description of hypothesis testing from a statistical point of view that I've ever encountered. I'll probably take it again, just to better understand the nuance and power.

  • Olesia
    11 days

  • Anne-Marie
    4 days

    In general, the course is really good. The only thing that annoys me is that in the exercises, always only one possibility of how to write a solution is accepted. This has often as a consequence that even though my answer is correct, I have to ask to show me the solution.

Oleksandr

"This was awesome"

Abu

Abdullah

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