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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

Concepts

Table of Contents (24) Chapters

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

Leave a review - let other readers know what you think

Index

Exercises

Practice the following exercises to revise the concept of reproducibility learned in this chapter:

Review: When we created the data frame from nothing, we combined a vector of 1,000 binomially distributed random variables, 1,000 normally distributed random variables, and a vector of two colors, red and white. Since all the columns in a data frame have to be the same length, how did R allow this? What is the property of vectors that allows this?
Seek out, read, and attempt to understand the source code of some of your favorite R packages. What version control system is the author of the package using?
Carefully review the analysis that was used as an example in this chapter. In what manner can this analysis be improved upon? Look at the distribution of the combined SAT scores in NYC schools. Why was modeling the SAT scores with a Gaussian likelihood function a very bad choice? What could we have done instead?
If both a poor and a rich person are willing to buy a pair of sneakers for...

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