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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


There were many new ideas introduced in this chapter, so kudos to you for making it through! You're well on the way to being able to tackle some extraordinarily interesting problems on your own!

To summarize, in this chapter, you learned that the relationships between two variables can be broken down into three broad categories.

For categorical/continuous variables, you learned how to use the by function to retrieve the statistics on the continuous variable for each category. We also saw how we can use box-and-whisker plots to visually inspect the distributions of the continuous variable across categories.

For categorical/categorical configurations, we used contingency and proportions tables to compare frequencies. We also saw how mosaic plots can help spot interesting aspects of the data that might be difficult to detect when just looking at the raw numbers.

For categorical/continuous data we discovered the concepts of covariance and correlations, and explored different correlation...

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