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Data Analysis with R, Second Edition - Second Edition

You're reading from  Data Analysis with R, Second Edition - Second Edition

Product type Book
Published in Mar 2018
Publisher Packt
ISBN-13 9781788393720
Pages 570 pages
Edition 2nd Edition
Languages
Toc

Table of Contents (24) Chapters close

Title Page
Copyright and Credits
Packt Upsell
Contributors
Preface
1. RefresheR 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 1. Other Books You May Enjoy Index

Summary


In this chapter, we took a detour through probability land. You learned some basic laws of probability, sample spaces, and conditional independence. You also learned how to derive Bayes' Theorem and learned that it provides the recipe to update hypotheses in the light of new evidence.

We also touched on the two primary interpretations of probability. In future chapters, we will be employing techniques from both these approaches.

We concluded with an introduction to sampling from distributions and used two—binomial and normal—distributions to answer interesting non-trivial questions about probability.

This chapter laid the important foundation that supports confirmatory data analysis. Making and checking inferences based on data is all about probability and, at this point, we know enough to move on to have a great time testing hypotheses with data!

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