course
A/B Testing in R
Intermediate
Updated 12/2024Start course for free
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RProbability & Statistics4 hours16 videos54 exercises4,400 XP2,060Statement of Accomplishment
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Course Description
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
2
Comparing Groups
3
Associations of Variables
4
Regression and Prediction
A/B Testing in R
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