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Biometry: The Principles and Practice of Statistics in Biological Research

Biometry: The Principles and Practice of Statistics in Biological Research 102 Reviews [Part 1, gene, considered in essence first by Francis Galton but still of considerable relevance. about the difficult and controversial idea of "genetic load". He also has something to say In short, this lecture clearly shows the importance of biomathematics as a young discipline. It would be interesting to know what aspects will be most exciting in 30 years' time. C. A. B. SMITH University College London 9. Biometry: the Principles and Practice of Statistics in Biological Research. By R. R. Sokal and F. J. Rohlf. San Francisco, W. H. Freeman & Co., 1969. xxi, 9f'. 126s. 776 p. In their Preface the authors state that this book "presents what we consider the mini­ mum required knowledge in statistics for a Ph.D. in the biological sciences at the present time". For a book of just under 800 pages this is at first sight rather a bold claim, but in this reveiwers's opinion it is well justified; full use of the book will permit the reader "at the very least to be an intelligent consulter of professional statisticians", which is more than can be said of most research students in the biological sciences. The first six chapters (125 pages) provide the background material for the main sections of the book, dealing with Data in Biology, the Handling of Data, Descriptive Statistics and the Binomial, Poisson and Normal Distributions. Chapter 7, Estimation and Hypo­ thesis Testing (49 pages), introduces the ideas of confidence limits and hypothesis testing and gives simple normal examples. Chapters 8-13 (230 pages) are devoted to the analysis of variance and contain a very full discussion of the elementary forms up to the three-way and higher order factorials. Models I and II are used from the first, the assumptions are discussed and the standard transformations considered: the authors believe that "a thorough foundation in analysis of variance is essential nowadays to every biologist" and these chapters can justifiably claim to provide this. Chapters 14 and 15 (146 pages) deal with regression and correlations: the discussion is elementary-multiple regression is mentioned as an advanced topic-but is thorough and is particularly good in dealing with the logical distinctions and difficulties of these techniques. Chapters 16 and 17 (95 pages), Analysis of Frequencies and Miscellaneous Methods, deal with such topics as tests of goodness of fit (X , G-test, Kolmogorov-Smirnov test), contingency tables, McNemar's test and Cochran's Q-test, combining probabilities from a series of tests and runs tests. There are four Appendices, the first (14 pages) giving various proofs not included in the text, the second (12 pages) on the Operation of Desk Calculators, and third (77 pages) being a package of statistical programs in FORTRAN IV and the fourth (9 pages) giving a Tabular Guide to Statistical Methods. There is a bibliography and a good index, but there are no statistical tables; these are published in a separate volume (Statistical Tables by Rohlf and Sokal). Great attention is given throughout to the details of computation and standard procedures are picked out in "boxes"; these boxes originated as mimeo­ graphed sheets handed out in lectures and contain sufficient detail to serve as model computations. There are homework exercises at the end of each chapter: some require substantial computation, because the authors believe that this is necessary to a full under­ standing of the methods. The style is direct and informal and makes for easy reading; this helps the book to be "as complete as possible for self-study". It is likely that biological students will need a fair amount of exhortation and encouragement before they can be persuaded to cover all the ground the authors regard as desirable, but this book should do a great deal to en­ courage them and to help them to understand biometrical reasoning as well as biometrical techniques. I certainly look forward to using it in my own graduate teaching. R. C. CAMPBELL School of Agriculture, Cambridge http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of the Royal Statistical Society Series A (Statistics in Society) Oxford University Press

Biometry: The Principles and Practice of Statistics in Biological Research

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Copyright
© 1970 The Authors
ISSN
0964-1998
eISSN
1467-985X
DOI
10.2307/2343822
Publisher site
See Article on Publisher Site

Abstract

102 Reviews [Part 1, gene, considered in essence first by Francis Galton but still of considerable relevance. about the difficult and controversial idea of "genetic load". He also has something to say In short, this lecture clearly shows the importance of biomathematics as a young discipline. It would be interesting to know what aspects will be most exciting in 30 years' time. C. A. B. SMITH University College London 9. Biometry: the Principles and Practice of Statistics in Biological Research. By R. R. Sokal and F. J. Rohlf. San Francisco, W. H. Freeman & Co., 1969. xxi, 9f'. 126s. 776 p. In their Preface the authors state that this book "presents what we consider the mini­ mum required knowledge in statistics for a Ph.D. in the biological sciences at the present time". For a book of just under 800 pages this is at first sight rather a bold claim, but in this reveiwers's opinion it is well justified; full use of the book will permit the reader "at the very least to be an intelligent consulter of professional statisticians", which is more than can be said of most research students in the biological sciences. The first six chapters (125 pages) provide the background material for the main sections of the book, dealing with Data in Biology, the Handling of Data, Descriptive Statistics and the Binomial, Poisson and Normal Distributions. Chapter 7, Estimation and Hypo­ thesis Testing (49 pages), introduces the ideas of confidence limits and hypothesis testing and gives simple normal examples. Chapters 8-13 (230 pages) are devoted to the analysis of variance and contain a very full discussion of the elementary forms up to the three-way and higher order factorials. Models I and II are used from the first, the assumptions are discussed and the standard transformations considered: the authors believe that "a thorough foundation in analysis of variance is essential nowadays to every biologist" and these chapters can justifiably claim to provide this. Chapters 14 and 15 (146 pages) deal with regression and correlations: the discussion is elementary-multiple regression is mentioned as an advanced topic-but is thorough and is particularly good in dealing with the logical distinctions and difficulties of these techniques. Chapters 16 and 17 (95 pages), Analysis of Frequencies and Miscellaneous Methods, deal with such topics as tests of goodness of fit (X , G-test, Kolmogorov-Smirnov test), contingency tables, McNemar's test and Cochran's Q-test, combining probabilities from a series of tests and runs tests. There are four Appendices, the first (14 pages) giving various proofs not included in the text, the second (12 pages) on the Operation of Desk Calculators, and third (77 pages) being a package of statistical programs in FORTRAN IV and the fourth (9 pages) giving a Tabular Guide to Statistical Methods. There is a bibliography and a good index, but there are no statistical tables; these are published in a separate volume (Statistical Tables by Rohlf and Sokal). Great attention is given throughout to the details of computation and standard procedures are picked out in "boxes"; these boxes originated as mimeo­ graphed sheets handed out in lectures and contain sufficient detail to serve as model computations. There are homework exercises at the end of each chapter: some require substantial computation, because the authors believe that this is necessary to a full under­ standing of the methods. The style is direct and informal and makes for easy reading; this helps the book to be "as complete as possible for self-study". It is likely that biological students will need a fair amount of exhortation and encouragement before they can be persuaded to cover all the ground the authors regard as desirable, but this book should do a great deal to en­ courage them and to help them to understand biometrical reasoning as well as biometrical techniques. I certainly look forward to using it in my own graduate teaching. R. C. CAMPBELL School of Agriculture, Cambridge

Journal

Journal of the Royal Statistical Society Series A (Statistics in Society)Oxford University Press

Published: Dec 5, 2018

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