New chapter on special topics that describes key features, such as processing by group, and explores importan
Trade Review
"The second edition of the book preserves the many good points of the first, and makes some improvements to the structure, e.g., on the graphical compendium. It also contains added material on more recent possibilities…is a good buy, if the goal is to have a reference book which allows to quickly find a way of accomplishing a task at hand in R, be it with or without RStudio."
— Ulrike Grömping, Beuth University of Applied Sciences Berlin, Journal of Statistical Software, November 2015
"… the book is easy to use. I have had it on my desk for the past few weeks and it has become invaluable. For those, like me, who find themselves regularly switching between R, MATLAB, and Python—or similar packages—it can save a lot of time."
—Significance Magazine, February 2016
Praise for the First Edition:This book is an excellent reference resource. Used this way, it can be helpful for years to come for both experienced and novice users. The organization of the material makes it easy to find the relevant piece of information either by topic (from the table of contents) or using one of the indexes. The task entries are self-contained. Users with experience in technical computing may use it as a quick starter in R, as well.
—Georgi N. Boshnakov, Journal of Applied Statistics, June 2012
This book provides a concise reference and annotated examples for R … . It is needed because R does not come with a coordinated manual … It is much easier to find information in Horton and Kleinman’s book because of their more detailed indices and table of contents. … Horton and Kleinman have succeeded very well in their goal of providing a concise reference manual and annotated examples. If you know the statistics (or can look them up) and have some experience using R, it is an extremely useful reference, and it has become my most consulted R book. … it would be an excellent reference for those wanting look up the syntax
Table of Contents
Data Input and Output. Data Management. Statistical and Mathematical Functions. Programming and Operating System Interface. Common Statistical Procedures. Linear Regression and ANOVA. Regression Generalizations and Modeling. A Graphical Compendium. Graphical Options and Configuration. Simulation. Special Topics. Case Studies. Appendices.
