SAS(r) System for Statistical Graphics, First Edition

by Michael Friendly

SAS System for Statistical Graphics is a book in the series of statistical applications guides published by SAS Institute. This book shows how to apply the SAS system to produce meaningful displays of statistical data. It emphasizes displays that reveal aspects of data not easily captured in numerical summaries or tabular formats and diagnostic displays that help determine if assumptions of an analysis are met. It is intended for users with basic to intermediate levels of experience with SAS software and statistics. It can also be useful to experienced SAS programmers who want to refine their use of statistical graphics and to researchers who want to apply modern methods of statistical graphics to their data.

The book contains almost 250 displays (over 50 in color), constructed with base SAS, SAS/GRAPH, SAS/IML and SAS/QC software. The SAS programs for most of the figures are explained. A collection of 15 graphical methods are implemented as general SAS macro programs which can be used with any set of data. The macro programs published in the book are available in one big file as The most current versions of these programs are maintained at sssg/.

Ordering Information

The book and macro program diskette are available through the Book Sales Department. You can place an order by telephone, by fax, by mail, or via the World Wide Web.
SAS Institute
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telephone orders: (919) 677-8000
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ISBN 1-55544-441-5  Order Number C56143  ($44.95)


Part 1: Introduction

Chapter 1 - Introduction to Statistical Graphics

Advantages of plotting data; The roles of graphics in data analysis; Psychological principles of data display; Graphical standards for data display; Strategies for graphical data analysis; Data sets.

Part 2: Univariate Displays

Chapter 2 - Graphical Methods for Univariate Data

Histograms and bar charts; Stem and leaf displays; Boxplots; Dot charts.

Chapter 3 - Plotting Theoretical and Empirical Distributions

Plotting theoretical statistical distributions; Bivariate normal distribution; Histogram smoothing and density estimation; Quantile plots; Plots for assessing symmetry.

Part 3: Bivariate Displays

Chapter 4 - Scatterplots

Simple scatterplots; Labelling observations; Interpolated curves and smoothings; Enhanced scatterplots; Plotting discrete data; Displaying a third variable on a scatterplot; Three-dimensional plots.

Chapter 5 - Plotting Regression Data

Plotting data, regression curves, and confidence limits; Regression with several groups; Validity of assumptions: plotting residuals; Partial regression plots; Multiple regression response surface; Plots of C(P) against P for variable selection; Regression with geographic data.

Part 4: Graphical Comparisons and Experimental Design Data

Chapter 6 - Comparing Groups

Quantile comparison plots for pairs of distributions; Comparative boxplots; Diagnostic plots for equalizing variability.

Chapter 7 - Plotting ANOVA Data

Plotting means in a one-way design; Plotting means for two-factor designs; Plotting interactions; Repeated measure designs; Displaying two-way tables for n=1 designs; Plotting power curves for ANOVA designs.

Part 5: Multivariate Data

Chapter 8 - Displaying Multivariate Data

Glyph plots; Draftsman's display and scatterplot matrix; Star plots; Profile plots; Andrews function plots; Biplot: plotting variables and observations together.

Chapter 9 - Multivariate Statistical Methods

Assessing multivariate normality; Detecting multivariate outliers; Plotting principal components and component scores; Discriminating among groups.

Chapter 10 - Displaying Categorical Data

Rectangular displays; Correspondence analysis.

Part 6: Appendices

Appendix 1 - Macro Programs

BIPLOT macro; BOXANNO macro; BOXPLOT macro; CONTOUR macro; CORRESP macro; DENSITY macro; DOTPLOT macro; LOWESS macro; NQPLOT macro; OUTLIER macro; PARTIAL macro; SCATMAT macro; STARS macro; SYMPLOT macro; TWOWAY macro.

Appendix 2 - Data Sets

Appendix 3 - Color output