Books applicable to the broadfield ofprogram evaluation are reviewed. Books may

be reviews singularly or in groups to illuminate similarities and dtrerences in intent,

philosophy, and usefulness. Persons with suggestions of books to be reviewed or

those who wish to submit a review should contact Barbara Searle (940 25th St.,

N.W., Apt. 114S, Washington, DC 20037) for specific instructions. In general, a

review of an individual book should not exceed four double-spaced typewritten

pages; groups of books may require additional length.

Gene Zelazny, Say It with Chub. Homewood, IL: Dow Jones-Irwin, 1985, 128

PP.

Hans Zeisel, Say It with Figures. New York: Harper & Row, 1985, 262 pp.

Reviewed by: MICHAEL HENDRICKS

I recently reviewed in this space three books on using graphics effectively (Hendricks,

1989). In that review I recommended Edward R. Tufte’s The Visual Display of

Quantitative Information and William S. Cleveland’s The Elements of Graphing Data,

but not Calvin F. Schmid’s Statistical Graphics. In the interim I’ve read the two additional books listed above, and I appreciate the

opportunity to pass along my reactions. Let me deal first with reading Zeisel’s book. Don’t. It’s as dull as Schmid’s book and even somewhat misleading. The “figures” in the title refer to numbers, tables, indices, statistical analyses, etc., not graphics.

Zelazny’s book, though, is an absolute “must read” as a solid introduction to using graphics. Zelazny was the Director of Visual Communications for the consulting

giant McKinsey & Company, and I can see why. He has the consultant’s talent for

Mkbael Hendricks l MH Associates, Washington, DC

Evaluation Practice. Vol. 11, No. 2, 1990, pp. 145-149 Copyright 0 1990 by JAI Press, Inc. ISSN: 0191-8036 All rights of reproduction in any form reserved.

145

146 Evaluation Practice, 11(2), 1990

spotting what the client/reader needs, explaining the different possibilities available, and then showing exactly how to use each possibility to its best advantage.

For example, Zelazny early on specifies what he calls “the five kinds of

comparison implied in any of the messages you’ll be deriving from tabular data”: (1)

Component (percentage of a total), (2) Item (ranking of items), (3) Time Series (changes over time), (4) Frequency Distribution (items within ranges), and (5) Correlation (relationship between variables).

Zelazny then introduces what he calls “the five basic chart forms”: ( 1) Pie charts,

(2) bar charts, (3) column charts, (4) line charts, and (5) dot charts. Then - and here’s where Zelazny shows his 20 years’ experience at simplifying complex messages - he

creates a matrix of these two dimensions and fills in each cell (visually, of course) with the proper chart form for each type of comparison. Like all effective graphics, this 5 x 5 matrix conveys a great deal of useful information all by itself.

Another plus of Zelazny’s book is his correct insistence that selecting the proper

graphic is only the third step in moving from data to graphics. He reminds us that the first and most important step is to:

Determine Your Message: The key to choosing the appropriate chart form is for you, as the designer, to be clear, first and foremost, about the specific point you want to make (emphasis in original).

I could mention other positive features of Zelazny’s book: its logical outline; its numerous examples (over 80) of different graphics; the author’s direct, engaging writing style; and the provocative section on why and how we should more often use paired-bar charts (instead of scatterplots) to show correlations. And, for those of us who learn better with hands-on practice, there are 21 pages of “work projects” and 56 pages filled with graphics examples.

Naturally, though, no book is perfect, and I could take exception with certain aspects of even this book. First, it is clearly an introductory book, and readers wanting a more sophisticated discussion should instead read Tufte and/or Cleveland. But, given the extremely poor use of graphics in most evaluation reports, many of us should probably start with these basic lessons before assuming we’re ready to advance.

Second, the actual amount of material included in the book is fairly meager, especially for an introductory book. Over and above the work projects and examples mentioned above, and eliminating the introduction, there are only 41 pages of text - and fairly sparse text at that. I can’t help but feel that a bit more material could have, and should have, been covered.

Finally, I disagree with Zelazny’s claim that there are only “five basic chart forms. ’ ’ In my training sessions we also discuss maps, small multiples, and pictographs, each of which can be uniquely appropriate in certain situations. And Zelazny’s omissions are even more glaring if we consider the many variations for using juxtaposition, multiple scales, and other enhancements of the five types of graphics he does discuss (see especially Cleveland’s book for these enhancements).

But now I’m quibbling, and this book deserves better, so let me summarize my recommendations. Avoid the Zeisel book, but definitely read Zelazny. As an

Book Reviews 147

introduction to the power of graphics and as a primer on developing the basic ones, this

book has no peer. It, along with Tufte’s and Cleveland’s books, belongs on every

evaluator’s bookshelf.

REFERENCE

Hendricks. M. ( 1989). Book reviews. Edrrr~tior~ Pwc~/~cY, /O(2). 68-73.

Lawrence B. Mohr, Impact Analysis for

Program Evaluation. Pacific Grove, CA: Brooks/Cole Publishing Company, 1988, 217

PP.

Reviewed by: JOSEPH S. WHOLEY

In a textbook that is also addressed to scholars, University of Michigan political

scientist Lawrence Mohr sets out to enhance students’ and practitioners’ understanding

of research design and valid casual inference. Here Mohr attempts a clearer, more

integrated treatment of topics explored by Campbell and Stanley ( 1963) and by Cook

and Campbell (1979). Hoping to contribute both to scholarly understanding and to

sound evaluation practice, Mohr uses the language of regression analysis to probe the

advantages and disadvantages of a dozen different experimental, quasi- experimental,

and pre-experimental designs that are often used in estimating program effects.

Although the book discusses many evaluations, its focus is confined to the logic of

causal inference, threats to valid inference, and ways to improve the validity of causal

inference. Intended for those who have studied statistics through multiple linear

regression, the book explores the development and testing of theories that programs

cause specific impacts, for example, achieving progress toward specific subobjec-

tives, objectives, or goals; for example, producing specific side-effects.

Joseph S. Wholey 0 Univcrrity o(‘ Southcm Calitbmiu: School of Puhlc Adminimation. Washington Public Al’l’air~ Ccntcr