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As one of the great statisticians of the century, Sir Maurice Kendall worked in areas covering an extraordinary range from intricate theory to detailed application.This memorial selection concentrates on a number of his less well known papers.They fall into four general groups.First are four papers concerned with applications, including his Presidential Address to the Royal Statistical Society.The next group consists of six paperson the theory of symmetric functions of sample observations.The third group includes a selection of Kendall's papers in the theory of ranking methods, including his 1938 discovery of the rank correlation coefficient since named after him.The last group of papers contains three of his early papers on the theory of time-series. General statistical readers as well as specialists will appreciate the book's sampling of Kendall's remarkable range of contributions. ... Read more

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Chapters: Peter Whittle, John Kingman, Maurice Kendall, Arthur Lyon Bowley, M. S. Bartlett, Calyampudi Radhakrishna Rao, George Alfred Barnard, David Cox, Richard Peto, George E. P. Box, Josiah Stamp, 1st Baron Stamp, Bernard Silverman, Dennis Lindley, David Spiegelhalter, Reginald Hawthorn Hooker, Howell Tong, Frank Kelly, Kantilal Mardia, Philip Dawid, David George Kendall, James Durbin, Gareth Roberts, John Nelder, David Clayton, George Henry Wood, Peter Donnelly, Henry Daniels, Peter Armitage, Harvey Goldstein, Michael Healy, Robin Plackett, Peter Green, Peter Mccullagh, Thomas A. Welton. Source: Wikipedia. Pages: 127. Not illustrated. Free updates online. Purchase includes a free trial membership in the publisher's book club where you can select from more than a million books without charge. Excerpt: Peter Whittle (born 27 February 1927, in Wellington, New Zealand) is a mathematician and statistician, working in the fields of stochastic nets, optimal control, time series analysis, stochastic optimization and stochastic dynamics. From 1967 to 1994, he was the Churchill Professor of Mathematics for Operational Research at the University of Cambridge. Whittle graduated from the University of New Zealand in 1947 with a B.Sc. in mathematics and physics and in 1948 with a M.Sc. in mathematics. He then moved to in 1950 to study for his Ph.D. with Herman Wold (at the University of Uppsala). His thesis, Hypothesis Testing in Time Series, generalized Wold's autoregressive representation theorem for univariate stationary processes to multivariate processes. Whittle's thesis was published in 1951. A synopsis of Whittle's thesis appeared also as an appendix to the second edition of Wold's book on time-series analysis. He remained in Uppsala at the Statistics Institute as a docent. In 1951 Whittle married Käthe Blomquist. In 1953, Whittle returned to New Zealand. In New Zealand, Whittle worked at the Department of Industrial and Sci...More: http://booksllc.net/?id=2600214 ... Read more

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Chapters: Maurice Kendall, William Farr, Reginald Hawthorn Hooker, George Paine, Stella Cunliffe, Goronwy Daniel. Source: Wikipedia. Pages: 29. Not illustrated. Free updates online. Purchase includes a free trial membership in the publisher's book club where you can select from more than a million books without charge. Excerpt: Sir Maurice George Kendall, FBA (6 September 1907 29 March 1983) was a British statistician, widely known for his contribution to statistics. The Kendall tau rank correlation is named after him. Maurice Kendall was born in Kettering, Northamptonshire as the only child of John Roughton Kendall and Georgina Brewer. As a young child he survived a case of cerebral meningitis, which was at the time frequently fatal. After growing up in Derby, England, he studied mathematics at St. John's College, Cambridge, where he played cricket and chess (with future champions Conel Hugh O'Donel Alexander and Jacob Bronowski). After graduation as a Mathematics Wrangler in 1929, he joined the British Civil Service in the Ministry of Agriculture. In this position he became increasingly interested in using statistics towards agricultural questions, and one of his first published papers to the Royal Statistical Society involved studying crop productivity using factor analysis. He was elected a Fellow of the Society in 1934. In 1938 and 1939 he began work, along with Bernard Babington-Smith, on the question of random number generation, developing both one of the first early mechanical devices to produce random digits, and formulated a series of tests for statistical randomness in a given set of digits which, with some small modifications, became fairly widely used. He produced one of the second large collections of random digits (100,000 in total, over twice as many as those published by L. H. C. Tippett in 1927), which was a commonly used tract until the publication of RAND Corporation's A Million Random Digits with 100,000...More: http://booksllc.net/?id=589136 ... Read more

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The original three-volume Advanced Theory of Statistics has long been regarded as the definitive work on statistical theory. The fifth edition of Volume I was published in 1987. Now, the fifth edition of Volume 2 is available. Considerably reshaped, this volume contains a great deal of new material and omits topics that will be treated in later volumes. Volumes 1 and 2 now present the essential topics that every statistician needs to know. These two core volumes will be supplemented in due course by a volume on Bayesian Inference and by a series of monographs on more specialized topics. Volume 2 covers the theory of estimation, testing hypotheses, regression, and comparative statistical inference.Part of the analysis of variance has been incorporated from Volume 3, which, with other chapters, provides a more complete treatment of the linear model than can be found anywhere else in the literature.This is a work that every statistician will find an invaluable source of insight and information. ... Read more

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Chapters: Ronald Fisher, Frank Yates, Francis Ysidro Edgeworth, Peter Whittle, Maurice Kendall, Charles Booth, Arthur Lyon Bowley, M. S. Bartlett, George Alfred Barnard, David Cox, Udny Yule, George E. P. Box, Harold Jeffreys, Austin Bradford Hill, Major Greenwood, Jerzy Neyman, Dennis Lindley, Robert Giffen, David George Kendall, James Durbin, Bernard Benjamin, John Nelder, R. G. D. Allen, Henry Daniels, Peter Armitage, Michael Healy, Egon Pearson, Robin Plackett. Source: Wikipedia. Pages: 125. Not illustrated. Free updates online. Purchase includes a free trial membership in the publisher's book club where you can select from more than a million books without charge. Excerpt: Sir Ronald Aylmer Fisher, FRS (17 February 1890 29 July 1962) was an English statistician, evolutionary biologist, eugenicist and geneticist. He was described by Anders Hald as "a genius who almost single-handedly created the foundations for modern statistical science," and Richard Dawkins described him as "the greatest of Darwin's successors". Fisher was born in East Finchley in London, England, to George and Katie Fisher. His father was a successful fine arts dealer. He had a happy childhood, being doted on by three older sisters, an older brother, and his mother, who died when Fisher was 14. His father lost his business in several ill-considered transactions only 18 months later. Although Fisher had very poor eyesight he was a precocious student, winning the Neeld Medal (a competitive essay in Mathematics) at Harrow School at the age of 16. Because of his poor eyesight, he was tutored in mathematics without the aid of paper and pen, which developed his ability to visualize problems in geometrical terms, as opposed to using algebraic manipulations. He was legendary in being able to produce mathematical results without setting down the intermediate steps. He also developed a strong interest in biology, and, especially, evolution. In 1909 he won a sch...More: http://booksllc.net/?id=140824 ... Read more

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Chapters: Maurice Kendall, Reginald Hawthorn Hooker, John Boreham, Douglas Macmillan, Eric Roll, Baron Roll of Ipsden, Andrew Cahn, Gerald Arbuthnot, Derek Barber, Baron Barber of Tewkesbury,. Source: Wikipedia. Pages: 35. Not illustrated. Free updates online. Purchase includes a free trial membership in the publisher's book club where you can select from more than a million books without charge. Excerpt: Sir Maurice George Kendall, FBA (6 September 1907 - 29 March 1983) was a British statistician, widely known for his contribution to statistics. The Kendall tau rank correlation is named after him. Maurice Kendall was born in Kettering, Northamptonshire as the only child of John Roughton Kendall and Georgina Brewer. As a young child he survived a case of cerebral meningitis, which was at the time frequently fatal. After growing up in Derby, England, he studied mathematics at St. John's College, Cambridge, where he played cricket and chess (with future champions Conel Hugh O'Donel Alexander and Jacob Bronowski). After graduation as a Mathematics Wrangler in 1929, he joined the British Civil Service in the Ministry of Agriculture. In this position he became increasingly interested in using statistics towards agricultural questions, and one of his first published papers to the Royal Statistical Society involved studying crop productivity using factor analysis. He was elected a Fellow of the Society in 1934. In 1938 and 1939 he began work, along with Bernard Babington-Smith, on the question of random number generation, developing both one of the first early mechanical devices to produce random digits, and formulated a series of tests for statistical randomness in a given set of digits which, with some small modifications, became fairly widely used. He produced one of the second large collections of random digits (100,000 in total, over twice as many as those published by L. H. C. Tippett in 1927), which was a commonly used tract...More: http://booksllc.net/?id=589136 ... Read more

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Second Edition of the classic on the subject. ... Read more

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Customer Reviews (1)

Very elementary level text
This text was written to give a rapid introduction to the topic to statistics students who are having conceptual difficulties with the idea of more than 3 spacelike dimensions.The idea of using geometric intuition to explain the interaction of multiple variables has been very fruitful in dimensions up to 3 and can be as extended as fruitfully to collections of more than 3 variables, if the reader can first get over the intellectual hurdle that says that geometry has to have some physical referrent.This book does a very good job on that account. It doesn't go very deeply into any aspect of the topic.Prerequisites are Calculus of several variables (partial derivatives), a first course in linear algebra and high school geometry.
A prospective reader who wants a deep understanding of the subject should really read Sommerville's An introduction to the geometry of n dimensions instead.Please note that Sommerville expects a higher level of knowlege of geometry and analysis than does Kendall. ... Read more

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This revision incorporates many textual changes, including the introduction of Ridge Regression. Exercises and numerous research results have also been added. ... Read more

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How to determine the unbiased estimator
As a grad student, Kendell and Stuart was the book I relied on in order to learn how to calculate the unbiased estimator of a population of statistical data.In elementary texts on statistics and data reduction you are given an inkling of this problem with regard to calculating a quantity such as the mean of a finite distribution.A real distribution differs from an ideal distribution in that its number of elements is finite rather than infinite.In order to compensate for the fact that the real distribution contains as few as N elements, the sum of a given value (e.g. position) for each element is divided by N-1 (instead of N for an ideal or infinite distribution) in order to better estimate the mean.In order to properly compensate for the finite number of elements of a real distribution, however, one needs to calculate the unbiased estimator of that distribution.The books teaches the reader the complex techniques, concepts, and statistical parameters such as cumulants that are used in compensating for the finite nature of real data. ... Read more

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The new edition of this classic reference includes a wealth of information on the mathematics and practical applications of rank correlation methods.It represents the most extensive revision since the book first appeared in 1948 and provides clear explanations of the methods of rank correlation widely used by statisticians, educators, psychologists, and others involved in analyzing qualitative material. Among the many topics covered are the Goodman-Kruskal coefficient, partial rank correlation, trend tests, and regression techniques.Real numerical examples and problems are taken from interesting research in the social sciences. Expanded tables have also been added that include larger sample sizes and a table of distribution of Kendall's partial law. Reflecting the vast amount of research published in recent years, this edition updates the references and offers over 300 new bibliographic entries.The valuable appendix tables have been revised and expanded. ... Read more