Joseph Schmuller - R All-in-One For Dummies

R All-in-One For Dummies

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Copyright 2023 by John Wiley & Sons, Inc., Hoboken, New Jersey

Published simultaneously in Canada

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Library of Congress Control Number: 2022950749

ISBN: 978-1-119-98369-9 (pbk); 978-1-119-98370-5 (ebk); 978-1-119-98371-2 (ebk)

1. Book 2 Chapter 1
2. Book 2 Chapter 3
3. Book 3 Chapter 1
4. Book 3 Chapter 2
5. Book 3 Chapter 3
6. Book 3 Chapter 4
7. Book 3 Chapter 5
8. Book 3 Chapter 6
9. Book 3 Chapter 7
10. Book 3 Chapter 8
11. Book 3 Chapter 9
12. Book 3 Chapter 10
13. Book 3 Chapter 11
14. Book 3 Chapter 12

1. Book 1 Chapter 1
2. Book 1 Chapter 2
3. Book 2 Chapter 1
4. Book 2 Chapter 2
5. Book 2 Chapter 5
6. Book 2 Chapter 6
7. Book 3 Chapter 1
8. Book 3 Chapter 2
9. Book 3 Chapter 3
10. Book 3 Chapter 4
11. Book 3 Chapter 5
12. Book 3 Chapter 6
13. Book 3 Chapter 7
14. Book 3 Chapter 8
15. Book 3 Chapter 9
16. Book 3 Chapter 10
17. Book 3 Chapter 11
18. Book 3 Chapter 12
19. Book 4 Chapter 1
20. Book 4 Chapter 2
21. Book 4 Chapter 3
22. Book 4 Chapter 4
23. Book 4 Chapter 5
24. Book 4 Chapter 6
25. Book 4 Chapter 7
26. Book 4 Chapter 8
27. Book 5 Chapter 1
28. Book 5 Chapter 2

In this book, Ive brought together all the information you need to hit the ground running with R. Its heavy on statistics, of course, because Rs creators built this language to analyze data.

So its necessary that you learn the foundations of statistics. Let me tell you at the outset: This All-in-One is not a cookbook. Ive never taught statistics that way and I never will. Before I show you how to use R to work with a statistical concept, I give you a strong grounding in what that concept is all about.

In fact, of this 5-book compendium are something like an introductory statistics text that happens to use R as a way of explaining statistical ideas.

gives you a set of projects that give you a chance to exercise your newly minted R skill set.

Want some more details? Read on.

The volume youre holding (or the e-book youre viewing) consists of five books that cover a lot of the length and breadth of R.

As I said earlier in this introduction, R is a language that deals with statistics. Accordingly, introduces you to the fundamental concepts of statistics that you just have to know in order to progress with R.

You then learn about R and RStudio, a widely used development environment for working with R. I begin by describing the rudiments of R code, and I discuss R functions and structures.

R truly comes alive when you use its specialized packages, which you learn about early on.

Part of working with statistics is to summarize data in meaningful ways. In , you find out how to do just that.

Most people know about averages and how to compute them. But thats not the whole story. In .

addresses the fundamental aim of statistical analysis: to go beyond the data and help you make decisions. Usually, the data are measurements of a sample taken from a large population. The goal is to use these data to figure out whats going on in the population.

This opens a wide range of questions: What does an average mean? What does the difference between two averages mean? Are two things associated? These are only a few of the questions I address in , and you learn to use the R tools that help you answer them.

Effective machine learning model creation comes with experience. Accordingly, in you gain experience by completing machine learning projects. In addition to the projects you complete along with me, I suggest additional projects for you to try on your own.