This contemporary presentation of statistical methods features
extensive use of graphical displays for exploring data and for
displaying the analysis. The authors demonstrate how to analyze
data—showing code, graphics, and accompanying tabular listings—for
all the methods they cover. They emphasize how to construct and
interpret graphs. They discuss principles of graphical design. They
identify situations where visual impressions from graphs may need
confirmation from traditional tabular results. All chapters have
exercises.
The authors provide and discuss R functions for all the new graphical
display formats. All graphs and tabular output in the book were
constructed using these functions. Complete R scripts for all examples
and figures are provided for readers to use as models for their own
analyses.
This book can serve as a standalone text for statistics majors at the
master’s level and for other quantitatively oriented disciplines at
the doctoral level, and as a reference book for researchers. In-depth
discussions of regression analysis, analysis of variance, and design
of experiments are followed by introductions to analysis of discrete
bivariate data, nonparametrics, logistic regression, and ARIMA time
series modeling. The authors illustrate classical concepts and
techniques with a variety of case studies using both newer graphical
tools and traditional tabular displays.
The Second Edition features graphs that are completely redrawn using
the more powerful graphics infrastructure provided by R's lattice
package. There are new sections in several of the chapters, revised
sections in all chapters and several completely new appendices.
New graphical material includes:
• an expanded chapter on graphics;
• a section on graphing Likert Scale Data to build on the importance of
rating scales in fields from population studies to psychometrics;
• a discussion on design of graphics that will work for readers with
color-deficient vision;
• an expanded discussion on the design of multi-panel graphics;
• expanded and new sections in the discrete bivariate statistics chapter
on the use of mosaic plots for contingency tables including the n×2×2
tables for which the Mantel–Haenszel–Cochran test is appropriate;
• an interactive (using the shiny package) presentation of the graphics
for the normal and t-tables that is introduced early and used in many
chapters.
The new appendices include discussions of R, the HH package
designed for R (the material in the HH package was distributed as a
set of standalone functions with the First Edition of this book), the
R Commander package, the RExcel system, the shiny package, and a
minimal discussion on writing R packages. There is a new appendix on
computational precision illustrating and explaining the FAQ
(Frequently Asked Questions) about the differences between the
familiar real number system and the less-familiar floating point
system used in computers. The probability distributions appendix has
been expanded to include more distributions (all the distributions in
base R) and to include graphs of each. The editing appendix from the
First Edition has been split into four expanded appendices—on working
style, writing style, use of a powerful editor, and use of LaTeX for
document preparation.
