perform an A/B Test for an ad campaign using python

Offered By
Coursera Project Network
In this Guided Project, you will:

Set up hypothesis testing

Perform an A/B Test

Clock2 hours
BeginnerBeginner
CloudNo download needed
VideoSplit-screen video
Comment DotsEnglish
LaptopDesktop only

By the end of this project, you will be able to apply statistics to perform an A/B Test for an ad campaign using python. A/B Testing is widely used by digital marketing agencies as it is the most effective mean to determine the best content to convert visits into sign-ups and purchases. Throughout the project, you will be able to set up hypothesis testing to advise a digital marketing agency that designed a new ad for their client on whether they should go for the new ad or not. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

Skills you will develop

A/B TestingPython ProgrammingData AnalysisStatistical Hypothesis TestingStatistics

Learn step-by-step

In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

  1. Load the dataset that we will work on

  2. Find insights in our data set up hypothesis testing

  3. compute the difference in the click through rate

  4. create sample distribution using bootstrapping

  5. evaluate the null hypothesis and draw conclusions.

How Guided Projects work

Your workspace is a cloud desktop right in your browser, no download required

In a split-screen video, your instructor guides you step-by-step

Frequently asked questions

Frequently Asked Questions

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