the elements of graphing data. william s. cleveland, hobart press, summit, new jersey, 1994. no. of...

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( 1997 by John Wiley & Sons, Ltd. STATISTICS IN MEDICINE, VOL. 16, 481 484 (1997) BOOK REVIEWS Editor: Niels Keiding 1. ¼. S. Cleveland, The Elements of Graphing Data. 2. R. ¸ehtonen and E. J. Pahkinen, Practical Methods for Design and Analysis of Complex Surveys. 3. C. C. Clogg and E. S. Shihadeh, Statistical Models for Ordinal Variables. Advanced Quantitative Techniques in the Social Sciences 4. 1. THE ELEMENTS OF GRAPHING DATA. William S. Cleveland, Hobart Press, Summit, New Jersey, 1994. No. of pages: 297. Price: £35 hardback. ISBN: 0-9634884-1-4 This is a fascinating book which sets out to encour- age good practice in the presentation of graphical information. Many of the suggestions in this book arise from recent developments in graphical percep- tion, an area to which the author has himself con- tributed. However, there are also many practical rules presented which arise from statistical issues. There are three main chapters in the book. Chapter 2 contains the principles of graph con- struction, first defining terminology, and then pre- senting a set of rules ‘use visually prominent graphical elements’, ‘don’t overdo the number of tick marks’, etc. Each of these rules is illustrated by an example, first showing a previously published graph reproduced exactly as it appeared in publi- cation, and then reformulated with the suggested rule applied to show the substantial improvement in clarity. These examples are very convincing, although occasionally the principles are too pre- scriptive. For example, many would disagree with the necessity of comprehensive captions describing conclusions, important features and details of every graphical item, and would prefer to place this information in the text. Chapter 3 consists of a selection of preferred graphical methods, covering such topics as dot plots, smoothers, coplots, scatter plot matrices and display of time series. There is some technical de- tail, but the emphasis is on understanding the graph and what it conveys to the reader. Some time is spent usefully discussing the confusion with what error bars represent in graphs, and suggests new graphical methods to avoid confusion be- tween the sample standard deviation and the stan- dard error of the mean. The chapter also contains a useful discussion of the choice of plotting sym- bols in identifying subgroups of the data in a scat- ter plot different types of circle fill are advised if there is little overlap of the points, whereas the use of texture symbols such as (L, #, (, s, w) is recommended where there is substantial overlap. The last chapter is the most fascinating, covering recent developments in graphical perception, and how these have been used to construct the prin- ciples in earlier chapters. Topics covered here in- clude a description of perception experiments be- hind the idea of texture symbols, mathematical arguments leading to the ‘banking to 45°’ rule for the display of time series, and a short section on perception of correlation in scatter plots. It finishes with an effective criticism of the widespread use of pie-charts and divided bar charts, and suggests that these be replaced by multiway dot plots. Col- our perception is discussed briefly, but this is prim- arily a book about graphics for the printed page, and only two of the many graphical displays are in colour. Intentionally, there is no discussion of software issues. Unsurprisingly, S was used to produce the graphics, but many graphs have been further modified, sometimes extensively, by other soft- ware. No opinion is expressed of the graphics out- put from other standard statistical packages such as SPSS and SAS. The book is well-produced and is a delight to read, although the style is somewhat leisurely at times. So many of the ideas seem self-evident, but the unamended published graphs used as examples provide a strong argument that this is not so. Everyone who reads this book will learn some- thing from it; in particular, it should be required reading for all graphical software writers and sci- entific journal editors. BRIAN FRANCIS Centre for Applied Statistics Fylde College Lancaster University Lancaster LA1 4YF, U.K.

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Page 1: THE ELEMENTS OF GRAPHING DATA. William S. Cleveland, Hobart Press, Summit, New Jersey, 1994. No. of pages: 297. Price: £35 hardback. ISBN: 0-9634884-1-4

( 1997 by John Wiley & Sons, Ltd.

STATISTICS IN MEDICINE, VOL. 16, 481—484 (1997)

BOOK REVIEWSEditor: Niels Keiding

1. ¼. S. Cleveland, The Elements of Graphing Data.

2. R. ¸ehtonen and E. J. Pahkinen, Practical Methods for Design and Analysis of Complex Surveys.

3. C. C. Clogg and E. S. Shihadeh, Statistical Models for Ordinal Variables. Advanced QuantitativeTechniques in the Social Sciences 4.

1. THE ELEMENTS OF GRAPHING DATA. William S.Cleveland, Hobart Press, Summit, New Jersey,1994. No. of pages: 297. Price: £35 hardback.ISBN: 0-9634884-1-4

This is a fascinating book which sets out to encour-age good practice in the presentation of graphicalinformation. Many of the suggestions in this bookarise from recent developments in graphical percep-tion, an area to which the author has himself con-tributed. However, there are also many practicalrules presented which arise from statistical issues.

There are three main chapters in the book.Chapter 2 contains the principles of graph con-struction, first defining terminology, and then pre-senting a set of rules — ‘use visually prominentgraphical elements’, ‘don’t overdo the number oftick marks’, etc. Each of these rules is illustrated byan example, first showing a previously publishedgraph reproduced exactly as it appeared in publi-cation, and then reformulated with the suggestedrule applied to show the substantial improvementin clarity. These examples are very convincing,although occasionally the principles are too pre-scriptive. For example, many would disagree withthe necessity of comprehensive captions describingconclusions, important features and details ofevery graphical item, and would prefer to place thisinformation in the text.

Chapter 3 consists of a selection of preferredgraphical methods, covering such topics as dotplots, smoothers, coplots, scatter plot matrices anddisplay of time series. There is some technical de-tail, but the emphasis is on understanding thegraph and what it conveys to the reader. Sometime is spent usefully discussing the confusion withwhat error bars represent in graphs, and suggestsnew graphical methods to avoid confusion be-tween the sample standard deviation and the stan-dard error of the mean. The chapter also containsa useful discussion of the choice of plotting sym-bols in identifying subgroups of the data in a scat-

ter plot — different types of circle fill are advised ifthere is little overlap of the points, whereas the useof texture symbols such as (L,#,(, s, w) isrecommended where there is substantial overlap.

The last chapter is the most fascinating, coveringrecent developments in graphical perception, andhow these have been used to construct the prin-ciples in earlier chapters. Topics covered here in-clude a description of perception experiments be-hind the idea of texture symbols, mathematicalarguments leading to the ‘banking to 45°’ rule forthe display of time series, and a short section onperception of correlation in scatter plots. It finisheswith an effective criticism of the widespread use ofpie-charts and divided bar charts, and suggeststhat these be replaced by multiway dot plots. Col-our perception is discussed briefly, but this is prim-arily a book about graphics for the printed page,and only two of the many graphical displays are incolour.

Intentionally, there is no discussion of softwareissues. Unsurprisingly, S was used to produce thegraphics, but many graphs have been furthermodified, sometimes extensively, by other soft-ware. No opinion is expressed of the graphics out-put from other standard statistical packages suchas SPSS and SAS.

The book is well-produced and is a delight toread, although the style is somewhat leisurely attimes. So many of the ideas seem self-evident, butthe unamended published graphs used as examplesprovide a strong argument that this is not so.Everyone who reads this book will learn some-thing from it; in particular, it should be requiredreading for all graphical software writers and sci-entific journal editors.

BRIAN FRANCIS

Centre for Applied StatisticsFylde College

Lancaster UniversityLancaster LA1 4YF, U.K.