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Introduction to A/B Testing in R

Learn A/B testing: including hypothesis testing, experimental design, and confounding variables.

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4 Hours16 Videos60 Exercises10,113 Learners4700 XP

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Course Description

In this course, you will learn the foundations of A/B testing, including hypothesis testing, experimental design, and confounding variables. You will also be exposed to a couple more advanced topics, sequential analysis and multivariate testing. The first dataset will be a generated example of a cat adoption website. You will investigate if changing the homepage image affects conversion rates (the percentage of people who click a specific button). For the remainder of the course you will use another generated dataset of a hypothetical data visualization website.
  1. 1

    Chapter 1: Mini case study in A/B Testing

    Free

    Short case study on building and analyzing an A/B experiment.

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    Introduction
    50 xp
    Goals of A/B testing
    50 xp
    Preliminary data exploration
    100 xp
    Baseline conversion rates
    50 xp
    Current conversion rate day of week
    100 xp
    Current conversion rate week
    100 xp
    Plotting conversion rate seasonality
    100 xp
    Experimental design, power analysis
    50 xp
    Randomized vs. sequential
    50 xp
    SSizeLogisticBin() documentation
    50 xp
    Power analysis August
    100 xp
    Power analysis August 5 percentage point increase
    100 xp

Datasets

Click datasetExperiment datasetData Visualization Website - April 2018

Collaborators

dcamposliz
David Campos
chester
Chester Ismay
shoninouye
Shon Inouye
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DataCamp Content Creator

Course Instructor

DataCamp offers interactive R, Python, Spreadsheets, SQL and shell courses. All on topics in data science, statistics, and machine learning. Learn from a team of expert teachers in the comfort of your browser with video lessons and fun coding challenges and projects.
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