Statistics for Biologists

This book has grown from nine hours oflectures, and about the same time in tutorial classes, that attempt to give first-year students of biology some understanding of statistics. This book has grown from nine hours oflectures, and about the same time in tutorial classes, that attempt to give first-year students of biology some understanding of statistics. I am convinced that such a short course should not be mathematical (though it can employ basic mathematical symbolism), and that it should give students an appreciation of statistical argument, even though this limits the amount of detailed instruction in techniques of analysis that can be included. A statistical cookery book would have been easier to write and much easier to read, but lacking in true educational content. I am more concerned to show 'why' than to present methods and rules. A further constraint, that of remaining within a reasonable price range, prevents reiteration of explanations: the reader is expected to remember what he has read, for he will not find standard terms and ideas explained afresh on each occasion of use. Many books that introduce statistics to biologists blur distinctions and evade logical issues, for example by failing to emphasize the distinction between a parameter and an estimator from a sample or by neglecting the role of randomization. On this, I aim to be un­ compromisingly correct - at least until reviewers point out my errors - but to do so through realistic examples rather than abstract symbolism.

An introduction to the principles and more elementary techniques of statistical reasoning. This is the third edition of a successful textbook, now with material added to illustrate the potential of computers for biologists. It is a lucid introduction to the principles and more elementary techniques of statistical reasoning, particularly as they are relevant to the biologist. Special attention is paid to the validity and use of statistical procedures, the interpretation of results, and the meanings of the conclusions which can then be drawn. The understanding of statistical methods is aided by full explanations of how calculations are built up. A particular feature of this edition is the inclusion, of new material to demonstrate the potential usefulness of computers in biological statistical analysis and to this end computer analyses of a selection of the examples are presented, using several different statistical languages. The examples are designed to guide and encourage the biologist to pursue the use of these languages further. The book assumes no mathematical training and uses a minimum of jargon and symbolism. It will be useful to any biologist, student or research worker who needs an introduction to statistical procedures.