Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Hands-On Data Science for Marketing

You're reading from   Hands-On Data Science for Marketing Improve your marketing strategies with machine learning using Python and R

Arrow left icon
Product type Paperback
Published in Mar 2019
Publisher Packt
ISBN-13 9781789346343
Length 464 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Author (1):
Arrow left icon
Yoon Hyup Hwang Yoon Hyup Hwang
Author Profile Icon Yoon Hyup Hwang
Yoon Hyup Hwang
Arrow right icon
View More author details
Toc

Table of Contents (20) Chapters Close

Preface 1. Section 1: Introduction and Environment Setup
2. Data Science and Marketing FREE CHAPTER 3. Section 2: Descriptive Versus Explanatory Analysis
4. Key Performance Indicators and Visualizations 5. Drivers behind Marketing Engagement 6. From Engagement to Conversion 7. Section 3: Product Visibility and Marketing
8. Product Analytics 9. Recommending the Right Products 10. Section 4: Personalized Marketing
11. Exploratory Analysis for Customer Behavior 12. Predicting the Likelihood of Marketing Engagement 13. Customer Lifetime Value 14. Data-Driven Customer Segmentation 15. Retaining Customers 16. Section 5: Better Decision Making
17. A/B Testing for Better Marketing Strategy 18. What's Next? 19. Other Books You May Enjoy

Statistical hypothesis testing

When you run A/B tests, it is important to test your hypothesis and seek for statistically significant differences among the test groups. Student's t-test, or simply the t-test, is frequently used to test whether the difference between two tests is statistically significant. The t-test compares the two averages and examines whether they are significantly different from each other.

There are two important statistics in a t-test—the t-value and p-value. The t-value measures the degree of difference relative to the variation in the data. The larger the t-value is, the more difference there is between the two groups. On the other hand, the p-value measures the probability that the results would occur by chance. The smaller the p-value is, the more statistically significant difference there will be between the two groups. The equation to...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image