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A/B Testing for Data Science (with Python & R)

Luke Lin
Data Science Academy Bootcamp Instructor
Panelist Spotlight

Luke obtained his doctorate in Mathematics at Stony Brook University, where he concentrated in partial differential equations. As a lifelong learner of mathematics, he is extremely efficient in quantitative analysis and also skilled at communicating abstract concepts. Being extremely passionate to share the insight of data from various industries, Luke looks forward to meeting curious students from all kinds of backgrounds enrolling at the Academy.

A/B Testing for Data Science (with Python and R)

|February 16, 2022|

Interested in learning Data Science but apprehensive about the statistics and coding requirements? This workshop will be an example of how you can confidently learn fundamental statistics and coding skills needed to understand and practice Data Science. In particular, you will learn the following important concepts: Statistics: A/B testing, hypothesis testing, p-value, permutations, and permutation test. Coding: variables, loops, and functions. We start by discussing “What is an A/B test?” and “Why do we use A/B testing?”, followed by several examples of A/B tests in Data Science. Then, we answer the main question of “How is an A/B test done?” with a detailed explanation of the steps involved in the A/B testing process (using didactic animations to illustrate those steps). Afterward, we introduce permutations and the Permutation Test as a good method to do the hypothesis testing part of an A/B test. We explain the Permutation Test process in detail, using didactic animations to illustrate the steps involved. Throughout this process, we provide intuitive explanations for hypothesis testing and the associated statistical concepts. In particular, we provide a clear graphical/visual interpretation of what is the p-value. Finally, we show how to code the learned concepts (from scratch) using both Python and R. This is an introductory-level webinar perfect for anyone interested in learning Data Science. You don’t need prior experience or background in coding nor statistics. Click here to get the materials for this workshop.