McCrimmon, having gotten Grierson's attention, continued: "A breakthrough, you say? If it's in economics, at least it can't be dangerous. Nothing like gene engineering, laser beams, sex hormones or international relations. That's where we don't want any breakthroughs. " (Galbraith, 1. K. (1990) A Tenured Profes sor, Houghton Mifflin; Boston. ) To judge astronomy] in this way a narrow utilitarian point of view] demon strates not only how poor we are, but also how small, narrow, and indolent our minds are; it shows a disposition always to calculate the payolTbefore the work, a cold heart and a lack of feeling for everything that is great and honors man. One can unfortunately not deny that such a mode of thinking is not uncommon in our age, and I am convinced that this is closely connected with the catastro phes which have befallen many countries in recent times; do not mistake me, I do not talk of the general lack of concern for science, but of the source from which all this has come, of the tendency to everywhere look out for one's advan tage and to relate everything to one's physical well-being, of the indilTerence towards great ideas, ofthe aversion to any elTort which derives from pure enthu siasm: I believe that such attitudes, if they prevail, can be decisive in catas trophes of the kind we have experienced. Gauss, K. F.: Astronomische An trittsvorlesung (cited from Buhler, W. K. (1981) Gauss: A Biographical Study, Springer: New York)]."

This is author-approved bcc: This is the third volume of a collection of seminal papers in the statistical science written during the past 110 years. These papers have each had an outstanding influence on the development of statistical theory and practice over the last century. Each paper is preceded by an introduction written by an authority in the field providing background information and assessing its influence. Volume III concertrates on articles from the 1980's while including some earlier articles not included in Volumes I and II. Samuel Kotz is Professor of Statistics in the College of Business and Management at the University of Maryland. Norman L. Johnson is Professor Emeritus of Statistics at the University of North Carolina. Also available: Breakthroughs in Statistics Volume I: Foundations and Basic Theory Samuel Kotz and Norman L. Johnson, Editors 1993. 631 pp. Softcover. ISBN 0-387-94037-5 Breakthroughs in Statistics Volume II: Methodology and Distribution Samuel Kotz and Norman L. Johnson, Editors 1993. 600 pp. Softcover. ISBN 0-387-94039-1

This is a two volume collection of seminal papers in the statistical sciences written during the past 100 years. These papers have each had an outstanding influence on the development of statistical theory and practice over the last century. Each paper is preceded by an introduction written by an authority in the field providing background information and assessing its influence. Readers will enjoy a fresh outlook on now well-established features of statistical techniques and philosophy by becoming acquainted with the ways they have been developed. It is hoped that some readers will be stimulated to study some of the references provided in the Introductions (and also in the papers themselves) and so attain a deeper background knowledge of the basis of their work.

Priced very competitively compared with other textbooks at this level! This gracefully organized textbook reveals the rigorous theory of probability and statistical inference in the style of a tutorial, using worked examples, exercises, numerous figures and tables, and computer simulations to develop and illustrate concepts. Beginning wi

"There is nothing like it on the market...no others are as encyclopedic...the writing is exemplary: simple, direct, and competent." —George W. Cobb, Professor Emeritus of Mathematics and Statistics, Mount Holyoke College Written in a direct and clear manner, Classic Topics on the History of Modern Mathematical Statistics: From Laplace to More Recent Times presents a comprehensive guide to the history of mathematical statistics and details the major results and crucial developments over a 200-year period. Presented in chronological order, the book features an account of the classical and modern works that are essential to understanding the applications of mathematical statistics. Divided into three parts, the book begins with extensive coverage of the probabilistic works of Laplace, who laid much of the foundations of later developments in statistical theory. Subsequently, the second part introduces 20th century statistical developments including work from Karl Pearson, Student, Fisher, and Neyman. Lastly, the author addresses post-Fisherian developments. Classic Topics on the History of Modern Mathematical Statistics: From Laplace to More Recent Times also features: A detailed account of Galton's discovery of regression and correlation as well as the subsequent development of Karl Pearson's X2 and Student's t A comprehensive treatment of the permeating influence of Fisher in all aspects of modern statistics beginning with his work in 1912 Significant coverage of Neyman–Pearson theory, which includes a discussion of the differences to Fisher’s works Discussions on key historical developments as well as the various disagreements, contrasting information, and alternative theories in the history of modern mathematical statistics in an effort to provide a thorough historical treatment Classic Topics on the History of Modern Mathematical Statistics: From Laplace to More Recent Times is an excellent reference for academicians with a mathematical background who are teaching or studying the history or philosophical controversies of mathematics and statistics. The book is also a useful guide for readers with a general interest in statistical inference.

Intercropping is an area of research for which there is a desperate need, both in developing countries where people are rapidly depleting scarce resources and still starving, and in developed countries, where more ecologically and economically sound ways of feeding ourselves must be developed. The only published guidelines for conducting such research and analyzing the data have been scattered about in various journal articles, many of which are hard to find. This book condenses these methods and will be immensely valuable to agricultural researchers and to the statisticians who help them design their experiments and interpret their results.

Included here are expressions in the functional domain of such classics as linear regression, principal components analysis, linear modelling, and canonical correlation analysis, as well as specifically functional techniques such as curve registration and principal differential analysis. Data arising in real applications are used throughout for both motivation and illustration, showing how functional approaches allow us to see new things, especially by exploiting the smoothness of the processes generating the data. The data sets exemplify the wide scope of functional data analysis; they are drawn from growth analysis, meteorology, biomechanics, equine science, economics, and medicine. The book presents novel statistical technology while keeping the mathematical level widely accessible. It is designed to appeal to students, applied data analysts, and to experienced researchers; and as such is of value both within statistics and across a broad spectrum of other fields. Much of the material appears here for the first time.