R for SAS and SPSS Users

Lavishly illustrated with both detailed line drawings and clinical photos, this book offers comprehensive coverage of every aspect of the management of intestinal stomas.

R is a powerful and free software system for data analysis and graphics, with over 5,000 add-on packages available. This book introduces R using SAS and SPSS terms with which you are already familiar. It demonstrates which of the add-on packages are most like SAS and SPSS and compares them to R's built-in functions. It steps through over 30 programs written in all three packages, comparing and contrasting the packages' differing approaches. The programs and practice datasets are available for download.

The glossary defines over 50 R terms using SAS/SPSS jargon and again using R jargon. The table of contents and the index allow you to find equivalent R functions by looking up both SAS statements and SPSS commands. When finished, you will be able to import data, manage and transform it, create publication quality graphics, and perform basic statistical analyses.

This new edition has updated programming, an expanded index, and even more statistical methods covered in over 25 new sections.

Uses clear, step-by-step demonstrations of every concept Uses SAS/SPSS terminology in narrative, Table of Contents, Index and Glossary Demonstrates which of over 5,000 add-on packages give the most SAS/SPSS-like output Includes supplementary material: sn.pub/extras

Autorentext

Robert A. Muenchen is the manager of the Statistical Consulting Center at the University of Tennessee and has 28 years of experience as a consulting statistician. He has served on the advisory boards of SPSS Inc. and the Statistical Graphics Corporation.

Inhalt
Introduction.- Installing and Updating R.- Running R.- Help and Documentation.- Programming Language Basics.- Data Acquisition.- Selecting Variables.- Selecting Observations.- Selecting Variables and Observations.- Data Management.- Enhancing Your Output.- Generating Data.- Managing Your Files and Workspace.- Graphics Overview.- Traditional Graphics- Graphics with ggplot2.- Statistics.- Conclusion.