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Data Analysis with R, Second Edition

You're reading from   Data Analysis with R, Second Edition A comprehensive guide to manipulating, analyzing, and visualizing data in R

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Product type Paperback
Published in Mar 2018
Publisher Packt
ISBN-13 9781788393720
Length 570 pages
Edition 2nd Edition
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Author (1):
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Tony Fischetti Tony Fischetti
Author Profile Icon Tony Fischetti
Tony Fischetti
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Table of Contents (19) Chapters Close

Preface 1. RefresheR FREE CHAPTER 2. The Shape of Data 3. Describing Relationships 4. Probability 5. Using Data To Reason About The World 6. Testing Hypotheses 7. Bayesian Methods 8. The Bootstrap 9. Predicting Continuous Variables 10. Predicting Categorical Variables 11. Predicting Changes with Time 12. Sources of Data 13. Dealing with Missing Data 14. Dealing with Messy Data 15. Dealing with Large Data 16. Working with Popular R Packages 17. Reproducibility and Best Practices 18. Other Books You May Enjoy

Who cares about coin flips


Who cares about coin flips? Well, virtually no one. However, (a) coin flips are a great simple application to get the hang of Bayesian analysis; (b) the kinds of problems that a beta prior and a binomial likelihood function solve go way beyond assessing the fairness of coin flips. We are now going to apply the same technique to a real life problem that I actually came across in my work.

For my job, I had to create a career recommendation system that asked the user a few questions about their preferences and spat out some careers they may be interested in. After a few hours, I had a working prototype. In order to justify putting more resources into improving the project, I had to prove that I was on to something and that my current recommendations performed better than chance.

In order to test this, we got 40 people together, asked them the questions, and presented them with two sets of recommendations. One was the true set of recommendations that I came up with,...

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