Descriptions
A/B Testing in R, 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.
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.
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.
What you’ll learn
- Build an Understanding of A/B Design
- Learn How to Analyze A/B Test Data
- Predict Outcomes Based on Data
- Present Results to Any Audience with Visualizations
Specificatoin of A/B Testing in R
- Publisher : Datacamp
- Teacher : Lauryn Burleigh
- Language : English
- Level : All Levels
- Number of Course : 4
- Duration : 4 hours to complete the cousre
Content of A/B Testing in R
Requirements
- Hypothesis Testing in R
Pictures
Sample Clip
Installation Guide
Extract the files and watch with your favorite player
Subtitle : English
Quality: 720p
Download Links
Password file(s): www.downloadly.ir
File size
93 MB