# The Book of R: A First Course in Programming and Statistics 1st Edition

| |**Pdf Book Name**: The Book of R: A First Course in Programming and Statistics 1st Edition

**Author**: Tilman M. Davies

**Publisher**: No Starch Press

**ISBN-10, 13**: 9781593276515, 978-1593276515

**Year**: 2016

**Pages**: 832 pages

**Language**: English

**File size**: 15 MB

**File format**: PDF,EPUB

## The Book of R: A First Course in Programming and Statistics 1st Edition Pdf Book Description:

R plays a key role in a wide variety of research and data analysis projects because it makes many modern statistical methods, both simple and advanced, readily available and easy to use. It’s true, however, that a beginner to R is often new to programming in general. As a beginner, you must not only learn to use R for your specific data analysis goals but also learn to think like a programmer. This is partly why R has a bit of a reputation for being “hard” but rest assured, that really isn’t the case. The Book of R is intended as a resource to help you get comfortable with R as a first programming language and with the statistical thought that underpins much of its use. The goal is to lay an introductory yet comprehensive foundation for understanding the computational nature of modern data science. The structure of the book seeks to progress naturally in content, first focusing on R as a computational and programming tool and then shifting gears to discuss using R for probability, statistics, and data exploration and modeling. You’ll build your knowledge up progressively, and at the end of each chapter, you’ll find a section summarizing the important code as a quick reference. Part I, which covers the fundamental syntax and object types used across all aspects of R programming, is essential for beginners.

Chapters 2 through 5 introduce the basics of simple arithmetic, assignment, and important object types such as vectors, matrices, lists, and data frames. In Chapter 6, I’ll discuss the way R represents missing data values and distinguishes among different object types. You’re given a primer on plotting in Chapter 7, using both built-in and contributed functionality (via the ggplot2 package—see Wickham, 2009); this chapter lays the groundwork for graphical design discussed later in the book. In Chapter 8, I’ll cover the fundamentals of reading data in from external files, essential for analysis of your own collected data. Part II focuses on getting you familiar with common R programming mechanisms. First, I’ll discuss functions and how they work in R in Chapter 9. Then, in Chapter 10, I’ll cover loops and conditional statements, which are used to control the flow, repetition, and execution of your code, before teaching you how to write your own executable R functions in Chapter 11. The examples in these two chapters are designed primarily to help you understand the behavior of these mechanisms rather than to present real world analyses. I’ll also cover some additional topics, such as error handling and measuring function execution time, in Chapter 12.

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