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Data Science for Decision Makers

You're reading from   Data Science for Decision Makers Enhance your leadership skills with data science and AI expertise

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Product type Paperback
Published in Jul 2024
Publisher Packt
ISBN-13 9781837637294
Length 270 pages
Edition 1st Edition
Languages
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Author (1):
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Jon Howells Jon Howells
Author Profile Icon Jon Howells
Jon Howells
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Table of Contents (20) Chapters Close

Preface 1. Part 1: Understanding Data Science and Its Foundations
2. Chapter 1: Introducing Data Science FREE CHAPTER 3. Chapter 2: Characterizing and Collecting Data 4. Chapter 3: Exploratory Data Analysis 5. Chapter 4: The Significance of Significance 6. Chapter 5: Understanding Regression 7. Part 2: Machine Learning – Concepts, Applications, and Pitfalls
8. Chapter 6: Introducing Machine Learning 9. Chapter 7: Supervised Machine Learning 10. Chapter 8: Unsupervised Machine Learning 11. Chapter 9: Interpreting and Evaluating Machine Learning Models 12. Chapter 10: Common Pitfalls in Machine Learning 13. Part 3: Leading Successful Data Science Projects and Teams
14. Chapter 11: The Structure of a Data Science Project 15. Chapter 12: The Data Science Team 16. Chapter 13: Managing the Data Science Team 17. Chapter 14: Continuing Your Journey as a Data Science Leader 18. Index 19. Other Books You May Enjoy

Walking through a case study

To consolidate all that we have learned in this chapter, let’s walk through the example we used at the beginning of the chapter about product promotion on an online store.

Let’s say we have data showing the daily sales volume for the 14 days before the promotion and the 14 days after the promotion. Our hypothesis is that the product’s daily sales have significantly increased following the promotion.

How could we use significance testing to test this hypothesis?

Let’s go through the steps we set out at the beginning of this chapter:

  1. Formulate the hypotheses: First, we need to state our null and alternative hypotheses.

    Question: Before reading on, can you try to formulate a null and alternative hypothesis?

    1. Null hypothesis (H0): Our null hypothesis is that there was no significant increase in average daily sales following the promotion.
    2. Alternative hypothesis (H1): Our alternative hypothesis is that there was a significant...
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