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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

Try out the following exercises to revise the concepts learned so far:

Look at the documentation on cor with help("cor"). You can see, in addition to "pearson" and "spearman", there is an option for "kendall". Learn about Kendall's tau. Why, and under what conditions, is it considered better than Spearman's rho?
For each species of iris, find the correlation coefficient between the sepal length and width. Are there any differences? How did we just combine two different types of the broad categories of bivariate analyses to perform a complex multivariate analysis?
Download a dataset from the web, or find another built-into-R dataset that suits your fancy (using library(help = "datasets")). Explore relationships between the variables that you think might have some connection.
Gustave Flaubert is well understood to be a classist misogynist and this, of course, influenced how he developed the character of Emma Bovary. However, it is not uncommon for the readers to identify and empathize...

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