Descriptions
A/B testing in R, A,B Testing is a common experimental design for human behavior research in industry and academia. A/B testing compares two variations to determine whether the measurement performs differently and whether the measurements vary in a meaningful way. Learning about A/B testing and presenting the results will help you make data-driven decisions and predictions.
In The Of course, you’ll learn what questions A/B testing can answer, what are the important considerations when conducting A/B testing, how to answer the questions at hand, and how to visualize the data. You’ll also learn how to determine the sample size needed for an experiment, how to conduct analyses appropriate to the data and hypotheses at hand, how to determine whether the results can be considered safe, and how to present the results to an audience regardless of statistical background.
The Courses Covers parametric and nonparametric 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. In addition, you will examine a power analysis for each test.
What you will learn
- build an understanding of A/B design
- learn How to analyze A/B test data
- predict Results based on data
- Currently Results for every audience with visualizations
Specifications for A/B testing in R
- Publisher : Data Camp
- Teacher: Lauryn Burleigh
- Language: English
- Level: All levels
- Number of courses: 4
- Duration: 4 hours to complete the course
Content of A/B tests in R
Requirements
Pictures
Sample clip
installation Guide
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Subtitles: English
Quality: 720p
Download links
Password file(s): free download software
File size
93MB