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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

Product type Paperback

Published in Mar 2018

Publisher Packt

ISBN-13 9781788393720

Length 570 pages

Edition 2nd Edition

Languages

R

Tools

ggplot

Concepts

Data Analysis

Author (1):

Tony Fischetti

View More author details

Table of Contents (19) Chapters

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

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Probability

It's time for us to put descriptive statistics down for the time being. It was fun for a while, but we're no longer content just determining the properties of observed data; now we want to start making deductions about data we haven't observed. This leads us to the realm of inferential statistics. In data analysis, probability is used to quantify uncertainty of our deductions about unobserved data. In the land of inferential statistics, probability reigns queen. Many regard her as a harsh mistress, but that's just a rumor.

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