课程
A/B Testing in R
中级技能水平
更新时间 2024年8月
RProbability & Statistics4小时16 视频54 道练习4,400 XP3,260成就证明
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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.
先决条件
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
课程完成 加入超过19百万学习者,今天就开始A/B Testing in R!
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