E. S. Keeping, Introduction to Statistical Inference (D. Van Nostrand Co., Princeton, N.J., 1962), xi + 451 pp., 66s.

Abstract

Professor Keeping's book is a text for a one-year course (90-100 hours) for students having a knowledge of elementary calculus-second or third year students.It is unusually complete in that it is difficult to think of a topic which is not treated, at least briefly, but which one might like to see included in such a course.As would be expected of a widely ranging book at this level, many results are stated without proof but it is by no means a " how to do it" book.In addition to the usual elementary probability theory, standard distributions, and classical estimation and testing, one finds, e.g. the cumulants and Ar-statistics, sampling techniques, sequential and nonparametric procedures, fixed, random and mixed models as well as latin square and incomplete block designs considered, and a last chapter which looks at multivariate problems and introduces stochastic processes.There is a laudable concern for the power of the tests discussed and the required non-central distributions are introduced.Appropriate tables, a large number of exercises (with answers) and a thirty page appendix on various mathematical topics are included as well.The price paid for the virtue of comprehensiveness is, of course, the brevity of some particular parts; one cannot have everything.However, one might reasonably suggest that the briefer the treatment the more precise should be the statements.This book is somewhat marred by puzzling, misleading, or false statements, e.g. both the sample and population moments are defined to be the " rth moment of X about zero"; "If T is sufficient, so is any function of T" (p.125); the variance of a maximum likelihood estimator is asserted to be the Cramer-Rao lower bound; in discussing the Mann-Whitney U-test, it is not clear at given points just what alternatives are being considered and while one statistic is described as the test statistic, we are instructed to reject for small values of another.