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Introduction to the analysis of metric spaces , by J. R. Giles. Pp 257. £25 (hardback), £8·95 (paperback). 1987. ISBN 0-521-35051-4, 35928-7 (Cambridge University Press)

These powerful computer packages are both a blessing and a curse to the practice and to the teaching of statistics. Now students can be given realistic data-sets to handle—no need to confine matters to two or three variables, with data already summarised as means and covariances. But the ease with which computations can now be handled ought to lead to more emphasis, in teaching, to the design of the statistical experiment, to the collection of the data, and to checking the data for outliers and errors. This book does include material on the use of Q-Q plots to assess normality of individual components but, to a large extent, it begins from the point that data, capable in principle of answering whatever question is being asked, are here, and how shall we use them. Students will need explicit guidance, to ask themselves how the data ought to have been collected, and what checks on its quality should be made, before embarking on the recommended analysis. Who will find the book useful? Anyone wishing to teach these multivariate techniques to whatever audience—mathematically strong, or mathematically merely competent—should seriously consider it as a main text. As well as the splendid data, there are many helpful diagrams, the mathematical results on which the techniques are based are stated clearly (and usually proved fully), and little space is taken up duplicating Statistical Tables the students ought to have anyway. This is a thorough, careful and balanced treatment that should attract many customers.