Computational Statistics & Data Analysis 1 (1983) 289-291 North-Holland

289

Book Reviews

Multivariate Data Analysis in Industrial Practice

by Paul J. LEWI John Wiley and Sons, Chichester, 1982 (256 pp., $29.95/£13.75, ISBN 0471 10466 3)

This text emphasizes the descriptive aspects of multivariate analysis. The author tries to show the reader how to use multivariate methods to display the information in a data table. The book contains chapters on tables and graphs, logarithm and power transformations, standardization of data, triangular plots, two-way analysis of variance, multiple regression, linear discriminant function analysis, geometric projections, relationships between distance and angles and correlation and covariance, factor analysis, and two-way graphs of the trans- formed results.

Real life data examples are used throughout which are mainly taken from the fields of pharmacology or economics. The data are not described very fully and often no clear motivating reason for the analysis is given to the reader. Fewer data sets that were more thoroughly discussed would have helped to tie the book together. This point is especially critical in this book because it is written for the practitioner and heavy emphasis has been placed on geometrical and visual interpretations of actual data.

Several factors make this book more difficult to read than other texts aimed at the same audience. Only elementary knowledge of calculus is assumed. On the other hand, all of the formulas are written in APL (A Programming Language by Ken Iverson) so the reader not familiar with APL continually has to translate back to regular algebra. The author states that he did it this way so the reader can go directly from the definitions to computer-executable statements. No mention is made of the many excellent packaged statistical programs (BMDP, SAS, SPSS-X, etc.) and the readers could get the impression that they have to program these techniques if they want to use them. Reference is made to a DATASCOPE package program that the author wrote but it is described very briefly.

Many of the explanations are not inclusive enough and are difficult to read. For example, in regression analysis no mention is made of the fixed effects model.

0167-9473/83/$3.00 © 1983, Elsevier Science Publishers B.V. (North-Holland)

290 Book Reviews

The reason for doing regression analysis is stated in a geometric argument using APL that many practitioners would find difficult to read. An example follows three pages later.

This book more resembles an interesting set of lecture notes that one would like to take a course from if the author taught the course. The geometric explanations and figures have been carefully worked out and provide an alternative explana- tion to the more usual matrix treatment of this subject.

Virginia Clark Dioision of Biostatistics University of California, Los Angeles Los Angeles, CA 90024, USA September 1983

The Visual Display of Quantitative Information by Edward R. TUFTE Graphics Press, Cheshire, CT, 1983 (190 pp., $32.00)

This beautiful text is devoted to the theory and practice in the design of statistical graphics. The first part of the book reviews the graphical practice of the two centuries since William Playfair (1759-1823), one of the great inventors of modern graphical design. Examples of graphical excellence include time-series, thematic maps, relational graphics, multivariate designs, and high density graph- ics. There are also a history and examples of graphical deception. The second part of the book provides a language for discussing graphics and a practical theory of data graphics. Principles such as "above all else show the data", "maximize the data-ink ratio (the proportion of data-ink to the total ink used to print the graphic)", "erase non-data-ink", "erase redundant data-ink", and "revise and edit" are illustrated with examples (both good and poor) of graphical work from 1700 to 1982. The theory that most of a graphic's ink should vary in response to data variation, is discussed with reference to numerous examples, from the workaday scientific chart to the recent inventions of Chernoff and Tukey. Discussion of the aesthetics in data graphical design leads to the conclusions that: