Fox - Using the R commander: a point-and-click interface for R

Using the R Commander

A Point-and-Click Interface for R

Chapman & Hall/CRC The R Series

Series Editors

John M. Chambers

Department of Statistics

Stanford University

Stanford, California, USA

Duncan Temple Lang

Department of Statistics

University of California, Davis

Davis, California, USA

Torsten Hothorn

Division of Biostatistics

University of Zurich

Switzerland

Hadley Wickham

RStudio

Boston, Massachusetts, USA

Aims and Scope

This book series reflects the recent rapid growth in the development and application of R, the programming language and software environment for statistical computing and graphics. R is now widely used in academic research, education, and industry. It is constantly growing, with new versions of the core software released regularly and more than 7,000 packages available. It is difficult for the documentation to keep pace with the expansion of the software, and this vital book series provides a forum for the publication of books covering many aspects of the development and application of R.

The scope of the series is wide, covering three main threads:

Applications of R to specific disciplines such as biology, epidemiology, genetics, engineering, finance, and the social sciences.

Using R for the study of topics of statistical methodology, such as linear and mixed modeling, time series, Bayesian methods, and missing data.

The development of R, including programming, building packages, and graphics.

The books will appeal to programmers and developers of R software, as well as applied statisticians and data analysts in many fields. The books will feature detailed worked examples and R code fully integrated into the text, ensuring their usefulness to researchers, practitioners and students.

Published Titles

Spatial Microsimulation with R, Robin Lovelace and Morgane Dumont

Statistics in Toxicology Using R, Ludwig A. Hothorn

Stated Preference Methods Using R, Hideo Aizaki, Tomoaki Nakatani, and Kazuo Sato

Using R for Numerical Analysis in Science and Engineering, Victor A. Bloomfield

Event History Analysis with R, Gran Brostrm

Computational Actuarial Science with R, Arthur Charpentier

Statistical Computing in C++ and R, Randall L. Eubank and Ana Kupresanin

Basics of Matrix Algebra for Statistics with R, Nick Fieller

Reproducible Research with R and RStudio, Second Edition, Christopher Gandrud

R and MATLAB, David E. Hiebeler

Nonparametric Statistical Methods Using R, John Kloke and Joseph McKean

Displaying Time Series, Spatial, and Space-Time Data with R, Oscar Perpin Lamigueiro

Programming Graphical User Interfaces with R, Michael F. Lawrence and John Verzani

Analyzing Sensory Data with R, Sbastien L and Theirry Worch

Parallel Computing for Data Science: With Examples in R, C++ and CUDA, Norman Matloff

Analyzing Baseball Data with R, Max Marchi and Jim Albert

Growth Curve Analysis and Visualization Using R, Daniel Mirman

R Graphics, Second Edition, Paul Murrell

Introductory Fisheries Analyses with R, Derek H. Ogle

Data Science in R: A Case Studies Approach to Computational Reasoning and Problem Solving, Deborah Nolan and Duncan Temple Lang

Multiple Factor Analysis by Example Using R, Jrme Pags

Customer and Business Analytics: Applied Data Mining for Business Decision Making Using R, Daniel S. Putler and Robert E. Krider

Implementing Reproducible Research, Victoria Stodden, Friedrich Leisch, and Roger D. Peng

Graphical Data Analysis with R, Antony Unwin

Using R for Introductory Statistics, Second Edition, John Verzani

Advanced R, Hadley Wickham

Dynamic Documents with R and knitr, Second Edition, Yihui Xie

Using the R Commander

A Point-and-Click Interface for R

John Fox

McMaster University

Hamilton, Ontario, Canada

CRC Press

Taylor & Francis Group

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2017 by Taylor & Francis Group, LLC

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Version Date: 20160524

International Standard Book Number-13: 978-1-4987-4190-3 (Paperback)

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To the memory of my mentor and friend, Mel Guyer.

Contents

The R Commander is a point-and-click graphical user interface (GUI) for R, providing access to R statistical software through familiar menus and dialog boxes instead of by typing potentially arcane commands. I expect that this book, which explains how to use the R Commander, will be of interest to students and instructors in introductory and intermediate-level statistics courses, to researchers who want to use R without having to contend with writing commands, and to R users who will eventually transition to the command-line interface but who prefer to start more simply.

In particular, in a basic statistics course, the central goal (in my opinion) should be to teach fundamental statistical ideasdistribution, statistical relationship, estimation, sampling variation, observational vs. experimental data, randomization, and so on. One doesnt want a basic statistics course to devolve into an exercise in learning how to write commands for statistical software, letting the software tail wag the statistical dog. I initially wrote the