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A start-to-finish guide to one of the most useful programming languages for researchers in a variety of fields.
In the newly revised Third Edition of The R Book, a team of distinguished teachers and researchers delivers a user-friendly and comprehensive discussion of foundational and advanced topics in the R software language, which is used widely in science, engineering, medicine, economics, and other fields. The book is designed to be used as both a complete text—readable from cover to cover—and as a reference manual for practitioners seeking authoritative guidance on particular topics.
This latest edition offers instruction on the use of the RStudio GUI, an easy-to-use environment for those new to R. It provides readers with a complete walkthrough of the R language, beginning at a point that assumes no prior knowledge of R and very little previous knowledge of statistics. Readers will also find
R is the most powerful tool in the known universe for carrying out statistical analysis, and it’s free! This book is aimed at those who wish to carry out such work – exploring, plotting, and modelling data – but who do not have much experience in R and/or statistics. R is described from scratch with instructions for loading and getting going with the software in Chapter 1 and a description of its essential elements in Chapter 3. Later chapters discuss statistical methods and are written so that they can be used either as a beginner’s guide or as a reference manual on particular procedures in
R. The theory behind the analyses is covered in enough depth, we hope, to make it comprehensible but without overburdening the reader with too much mathematics.
Using R has become far simpler with the introduction of RStudio, which is also free (other editors are available). RStudio provides a friendly front end and easy access to tools, all of which seem a long way from R’s original rather forbidding command prompt. This book assumes the use of RStudio rather than using R directly, but the code presented will work using the latter setup too.
A thorough introduction to fundamental concepts in statistics and step-by-step roadmaps to their implementation in R
Comprehensive explorations of worked examples in R
A complementary companion website with downloadable datasets that are used in the book
In-depth examination of essential R packages.
Perfect for undergraduate and postgraduate students of science, engineering, medicine economics, and geography, The R Book will also earn a place in the libraries of social sciences professionals.
True PDF
Getting Started
Technical Background
Essentials of the R Language
Data Input and Dataframes
Graphics
Graphics in More Detail
Tables
Probability Distributions in R
Testing
Regression
Generalised Linear Models
Generalised Additive Models
Mixed-Effect Models
Non-linear Regression
Survival Analysis
Designed Experiments
Meta-Analysis
Time Series
Multivariate Statistics
Classification and Regression Trees
Spatial Statistics
Bayesian Statistics