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Cookbook for R: Best R Programming TIPs
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• Title: Cookbook for R: Best R Programming TIPs
• Author(s) Winston Chang
• Publisher: cookbook-r.com; eBook (Creative Commons Licensed)
• License(s): CC BY-SA 3.0, CC0 1.0
• Paperback: 616 pages
• eBook: HTML
• Language: English
• ISBN-10: N/A
• ISBN-13: 978-1326189723

Book Description

The goal of this cookbook is to provide solutions to common tasks and problems in analyzing data. Each recipe tackles a specific problem with a solution you can apply to your own project, and includes a discussion of how and why the recipe works.

Each recipe addresses a specific problem and includes a discussion that explains the solution and provides insight into how it works. If you're a beginner, this book will help get you started. If you're an intermediate user, this book will jog your memory and expand your horizons. You'll get the job done faster and learn more about R in the process.

R is a powerful tool for statistics, graphics, and statistical programming. It is used by tens of thousands of people daily to perform serious statistical analyses. It is a free, open source system whose implementation is the collective accomplishment of many intelligent, hard-working people.

At its core, this is an introductory statistics textbook pitched primarily at psychology students. As such, it covers the standard topics that you'd expect of such a book: study design, descriptive statistics, the theory of hypothesis testing, t-tests, X2 tests, ANOVA and regression.

• Create vectors, handle variables, and perform other basic functions
• Simplify data input and output
• Tackle data structures such as matrices, lists, factors, and data frames
• Work with probability, probability distributions, and random variables
• Calculate statistics and confidence intervals and perform statistical tests
• Create a variety of graphic displays
• Build statistical models with linear regressions and analysis of variance (ANOVA)
• Explore advanced statistical techniques, such as finding clusters in your data
• WWinston Chang is a software engineer at RStudio, where he works on data visualization and software development tools for R. He has a Ph.D. in Psychology from Northwestern University, and created the Cookbook for R website, which contains recipes for common tasks in R.
• R Cookbook: Recipes for Data Analysis, Statistics, and Graphics

This book is full of how-to recipes, each of which solves a specific problem. Each recipe includes a quick introduction to the solution followed by a discussion that aims to unpack the solution and give you some insight into how it works.

• R Graphics Cookbook: Practical Recipes for Visualizing Data

This cookbook provides more than 150 recipes to help scientists, engineers, programmers, and data analysts generate high-quality graphs quickly - without having to comb through all the details of R's graphing systems.

• R Packages: Organize, Test, Document, and Share Your Code

Turn your R code into packages that others can easily download and use. This practical book shows you how to bundle reusable R functions, sample data, and documentation together by applying author's package development philosophy.

• An Introduction to R (Alex Douglas, et al.)

The main aim of this book is to help you climb the initial learning curve and provide you with the basic skills and experience (and confidence!) to enable you to further your experience in using R.

• R for Data Science: Visualize, Model, Transform, Tidy, Import

This book teaches you how to do data science with R: You'll learn how to get your data into R, get it into the most useful structure, transform it, visualize it and model it, how data science can help you work with the uncertainty and capture the opportunities.

This book aims at giving a wide understanding of many aspects of R. Combining detailed explanations with real-world examples and exercises, this book will provide you with a solid understanding of both statistics and the depth of R's functionality.

• Applied Statistics with R (David Dalpiaz)

This book provides an integrated treatment of statistical inference techniques in data science using the R Statistical Software. It provides a much-needed, easy-to-follow introduction to statistics and the R programming language.

This book helps you understand how R works at a fundamental level. Designed for R programmers who want to deepen their understanding of the language, and programmers experienced in other languages to understand what makes R different and special.

• Advanced R Solutions (Malte Grosser, et al)

This book offers solutions to the exercises from Advanced R, 2nd Edition by Hadley Wickham. It is work in progress and under active development. The 2nd edition of Advanced R is in print now and we hope to provide most of the answers.

• Advanced Data Analysis using R (Cosma R. Shalizi)

This is a textbook on data analysis methods, intended for advance undergraduate students who have already taken classes in probability, mathematical statistics, and linear regression. All examples implemented using R.

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