98 BOOK REVIEWS 2. BASIC STATISTICS FOR LABORATORIES. A PRIMER FOR LABORATORY WORKERS. William D. Kelley, Thomas A. Ratliff Jr. and Charles Nenadic, New York, van Nostrand Reinhold, 1992. No. of pages: ix + 175. Price: €32.50. ISBN 0-442-00456-7 It is a strange book on statistics for laboratories that does not mention reference intervals (normal ranges) or the evaluation and comparison of methods of measurement (although the latter topic is promised on the back cover). Although the book is not meant specifically for medical laboratory workers they are included among those for whom the book is intended, and so these omissions are remarkable. Of the 170 pages of text 36 are de- voted to quality control and a staggering 62 to outliers. Only 26 pages are given over to standard statistical methods (largely t, x2, correlation and linear regression), and nine of these pages are tables. I get the strong impression that most of the book was written 20 years ago: a lot of attention is given to outdated or irrelevant methods, such as estimating the standard deviation from the range; there is almost no mention of computers but occa- sional references to desk calculators; and most of the references are pre-1970. None of these eccentricitieswould be too serious if the book was otherwise correct and clear, but it is neither. Many statements about statistical methods are misleading or incorrect. The very brief section on the Poisson distribution is a master- piece of uselessness. The chapter on significance tests manages to omit any mention of P values. In addition to several errors in formulae there is a cavalier attitude to mathematical notation: capital and lower case letters are often used interchange- ably, subscripts are treated ambiguously (F = ab2/aa2 rather than a:/ut) and Cs and bars (for means) are often omitted (as in CV = u/X). Also, x2 frequently appears as K but also as X and x2. It seems unlikely that the book could have been proof read. Most of the data sets appear fictitious and some are irrelevant too. (Surely there is no valid reason for making up irrelevant data.) Thus the Poisson distribution is illustrated using data about horses losing shoes, and linear regression by data on the height and diameter of trees. The graph of the latter data has the X and Y variables reversed, and only four of the 20 points lie above the incorrectly drawn regression line. The equation for the re- sidual standard deviation contains several errors, so it is perhaps just as well that the use to which this quantity might be put is not divulged to readers. The inclusion of dozens of methods for dealing with outliers gives a distorted view of their import- ance. Here, as elsewhere, the methods are pre- sented in a cookbook manner, so that the reader will not gain insight into the underlying statistical principles. The coverage of quality control may be better - this is probably where the authors have most expertise - but in view of the serious prob- lems already noted I could not recommend that anyone relies on this section either. This book is very far from being the timely and essential reference claimed on the back cover. It has gone straight into my chamber of horrors. DOUGLAS G. ALTMAN Medical Statistics Laboratory Imperial Cancer Research Fund P.O. Box 123 Lincoln’s Inn Fieldr London WC2A 3PX. U.K.

Basic statics for laboratories. A primer forlaboratory workers. William D. Kelley, Thomas A. Ratiff Jr. and Charles Nenadic, New York, van Nostrand Reinhold, 1992. No. of pages: ix

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Page 1: Basic statics for laboratories. A primer forlaboratory workers. William D. Kelley, Thomas A. Ratiff Jr. and Charles Nenadic, New York, van Nostrand Reinhold, 1992. No. of pages: ix

98 BOOK REVIEWS

2. BASIC STATISTICS FOR LABORATORIES. A PRIMER FOR LABORATORY WORKERS. William D. Kelley, Thomas A. Ratliff Jr. and Charles Nenadic, New York, van Nostrand Reinhold, 1992. No. of pages: ix + 175. Price: €32.50. ISBN 0-442-00456-7

It is a strange book on statistics for laboratories that does not mention reference intervals (normal ranges) or the evaluation and comparison of methods of measurement (although the latter topic is promised on the back cover). Although the book is not meant specifically for medical laboratory workers they are included among those for whom the book is intended, and so these omissions are remarkable. Of the 170 pages of text 36 are de- voted to quality control and a staggering 62 to outliers. Only 26 pages are given over to standard statistical methods (largely t , x 2 , correlation and linear regression), and nine of these pages are tables. I get the strong impression that most of the book was written 20 years ago: a lot of attention is given to outdated or irrelevant methods, such as estimating the standard deviation from the range; there is almost no mention of computers but occa- sional references to desk calculators; and most of the references are pre-1970.

None of these eccentricities would be too serious if the book was otherwise correct and clear, but it is neither. Many statements about statistical methods are misleading or incorrect. The very brief section on the Poisson distribution is a master- piece of uselessness. The chapter on significance tests manages to omit any mention of P values. In addition to several errors in formulae there is a cavalier attitude to mathematical notation: capital and lower case letters are often used interchange- ably, subscripts are treated ambiguously (F = ab2/aa2 rather than a:/ut) and Cs and bars (for

means) are often omitted (as in CV = u/X). Also, x 2 frequently appears as K but also as X and x2. It seems unlikely that the book could have been proof read.

Most of the data sets appear fictitious and some are irrelevant too. (Surely there is no valid reason for making up irrelevant data.) Thus the Poisson distribution is illustrated using data about horses losing shoes, and linear regression by data on the height and diameter of trees. The graph of the latter data has the X and Y variables reversed, and only four of the 20 points lie above the incorrectly drawn regression line. The equation for the re- sidual standard deviation contains several errors, so it is perhaps just as well that the use to which this quantity might be put is not divulged to readers.

The inclusion of dozens of methods for dealing with outliers gives a distorted view of their import- ance. Here, as elsewhere, the methods are pre- sented in a cookbook manner, so that the reader will not gain insight into the underlying statistical principles. The coverage of quality control may be better - this is probably where the authors have most expertise - but in view of the serious prob- lems already noted I could not recommend that anyone relies on this section either.

This book is very far from being the timely and essential reference claimed on the back cover. It has gone straight into my chamber of horrors.

DOUGLAS G. ALTMAN Medical Statistics Laboratory

Imperial Cancer Research Fund P.O. Box 123

Lincoln’s Inn Fieldr London WC2A 3PX. U.K.