Course
A/B Testing in R
IntermediateSkill Level
Updated 08/2024
RProbability & Statistics4 hr16 videos54 Exercises4,400 XP3,228Statement of Accomplishment
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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 R1
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.
2
Comparing Groups
Learn common analyses to compare A/B groups. Understand the appropriate approach to each test given their assumptions and limitations.
3
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.
4
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.
A/B Testing in R
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FAQs
What statistical methods for A/B testing does this course teach?
You will learn group comparison tests, association analysis, trend analysis, and regression-based prediction, along with how to choose the right test based on data assumptions and limitations.
Do I need prior experience with hypothesis testing to take this course?
Yes. Hypothesis Testing in R and Sampling in R are prerequisites. The course builds on these foundations to apply them specifically to A/B test scenarios.
Will I learn how to determine sample size for an A/B test?
Yes. The course teaches you how to calculate the sample size needed for an experiment so you can ensure your results are statistically reliable.
Does the course cover how to present A/B test results to non-technical audiences?
Yes. You will learn to visually present regression results and communicate findings to audiences regardless of their statistical background.
What types of jobs use A/B testing skills?
A/B testing is widely used by product managers, data analysts, UX researchers, and growth marketers in both tech companies and academic research settings.
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