Leading Personalities In Statistical Sciences
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| Author | : Norman L. Johnson |
| Publisher | : John Wiley & Sons |
| Total Pages | : 432 |
| Release | : 2011-09-26 |
| Genre | : Mathematics |
| ISBN | : 1118150724 |
A fascinating chronicle of the lives and achievements of the menand women who helped shapethe science of statistics This handsomely illustrated volume will make enthralling readingfor scientists, mathematicians, and science history buffs alike.Spanning nearly four centuries, it chronicles the lives andachievements of more than 110 of the most prominent names intheoretical and applied statistics and probability. From Bernoullito Markov, Poisson to Wiener, you will find intimate profiles ofwomen and men whose work led to significant advances in the areasof statistical inference and theory, probability theory, governmentand economic statistics, medical and agricultural statistics, andscience and engineering. To help readers arrive at a fullerappreciation of the contributions these pioneers made, the authorsvividly re-create the times in which they lived while exploring themajor intellectual currents that shaped their thinking andpropelled their discoveries. Lavishly illustrated with more than 40 authentic photographs andwoodcuts * Includes a comprehensive timetable of statistics from theseventeenth century to the present * Features edited chapters written by 75 experts from around theglobe * Designed for easy reference, features a unique numbering schemethat matches the subject profiled with his or her particular fieldof interest
| Author | : Samuel Kotz |
| Publisher | : Springer My Copy UK |
| Total Pages | : 680 |
| Release | : 1992 |
| Genre | : Mathematical statistics |
| ISBN | : 9781461209201 |
Volume III includes more selections of articles that have initiated fundamental changes in statistical methodology. It contains articles published before 1980 that were overlooked in the previous two volumes plus articles from the 1980's - all of them chosen after consulting many of today's leading statisticians.
| Author | : William Q. Meeker |
| Publisher | : John Wiley & Sons |
| Total Pages | : 783 |
| Release | : 2014-08-21 |
| Genre | : Mathematics |
| ISBN | : 1118625978 |
Amstat News asked three review editors to rate their top five favorite books in the September 2003 issue. Statistical Methods for Reliability Data was among those chosen. Bringing statistical methods for reliability testing in line with the computer age This volume presents state-of-the-art, computer-based statistical methods for reliability data analysis and test planning for industrial products. Statistical Methods for Reliability Data updates and improves established techniques as it demonstrates how to apply the new graphical, numerical, or simulation-based methods to a broad range of models encountered in reliability data analysis. It includes methods for planning reliability studies and analyzing degradation data, simulation methods used to complement large-sample asymptotic theory, general likelihood-based methods of handling arbitrarily censored data and truncated data, and more. In this book, engineers and statisticians in industry and academia will find: A wealth of information and procedures developed to give products a competitive edge Simple examples of data analysis computed with the S-PLUS system-for which a suite of functions and commands is available over the Internet End-of-chapter, real-data exercise sets Hundreds of computer graphics illustrating data, results of analyses, and technical concepts An essential resource for practitioners involved in product reliability and design decisions, Statistical Methods for Reliability Data is also an excellent textbook for on-the-job training courses, and for university courses on applied reliability data analysis at the graduate level. An Instructor's Manual presenting detailed solutions to all the problems in the book is available upon requestfrom the Wiley editorial department.
| Author | : Vijay K. Rohatgi |
| Publisher | : John Wiley & Sons |
| Total Pages | : 747 |
| Release | : 2011-09-15 |
| Genre | : Mathematics |
| ISBN | : 1118165683 |
The second edition of a well-received book that was published 24 years ago and continues to sell to this day, An Introduction to Probability and Statistics is now revised to incorporate new information as well as substantial updates of existing material.
| Author | : Otto J.W.F. Kardaun |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 416 |
| Release | : 2005-09-16 |
| Genre | : Science |
| ISBN | : 9783540211150 |
Classical Methods of Statistics is a guidebook combining theory and practical methods. It is especially conceived for graduate students and scientists who are interested in the applications of statistical methods to plasma physics. Thus it provides also concise information on experimental aspects of fusion-oriented plasma physics. In view of the first three basic chapters it can be fruitfully used by students majoring in probability theory and statistics. The first part deals with the mathematical foundation and framework of the subject. Some attention is given to the historical background. Exercises are added to help readers understand the underlying concepts. In the second part, two major case studies are presented which exemplify the areas of discriminant analysis and multivariate profile analysis, respectively. To introduce these case studies, an outline is provided of the context of magnetic plasma fusion research. In the third part an overview is given of statistical software; separate attention is devoted to SAS and S-PLUS. The final chapter presents several datasets and gives a description of their physical setting. Most of these datasets were assembled at the ASDEX Upgrade Tokamak. All of them are accompanied by exercises in form of guided (minor) case studies. The book concludes with translations of key concepts into several languages.
| Author | : Vic Barnett |
| Publisher | : John Wiley & Sons |
| Total Pages | : 418 |
| Release | : 1999-08-03 |
| Genre | : Mathematics |
| ISBN | : 9780471976431 |
This fully updated and revised third edition, presents a wide ranging, balanced account of the fundamental issues across the full spectrum of inference and decision-making. Much has happened in this field since the second edition was published: for example, Bayesian inferential procedures have not only gained acceptance but are often the preferred methodology. This book will be welcomed by both the student and practising statistician wishing to study at a fairly elementary level, the basic conceptual and interpretative distinctions between the different approaches, how they interrelate, what assumptions they are based on, and the practical implications of such distinctions. As in earlier editions, the material is set in a historical context to more powerfully illustrate the ideas and concepts. Includes fully updated and revised material from the successful second edition Recent changes in emphasis, principle and methodology are carefully explained and evaluated Discusses all recent major developments Particular attention is given to the nature and importance of basic concepts (probability, utility, likelihood etc) Includes extensive references and bibliography Written by a well-known and respected author, the essence of this successful book remains unchanged providing the reader with a thorough explanation of the many approaches to inference and decision making.
| Author | : Samuel Kotz |
| Publisher | : John Wiley & Sons |
| Total Pages | : 690 |
| Release | : 1997-04-11 |
| Genre | : Mathematics |
| ISBN | : 9780471155744 |
In honor of Samuel Kotz, an international collection of articles on the latest advances in statistics. This tribute to Samuel Kotz features articles by eminent statisticians from around the world, all recognizing the lifetime of accomplishments of one of the premier statisticians of our time. Centered on distributions, models, and their applications, this book highlights some recent developments in both theory and applications of statistics. Editors Norman L. Johnson and N. Balakrishnan, both of whom have collaborated extensively with Samuel Kotz, have gathered contributions from theoreticians and practitioners in 18 countries, giving the volume a global perspective. Each article is classified into one of 10 areas in the theory and practice of statistics. The areas highlighted in this volume are: Statistics in the world. Models. Biostatistics. Testing and estimation. Univariate distributions. Multivariate distributions. Characterizations. Probability. Bayes theory. Descriptive statistics. Many of the articles in the volume highlight Samuel Kotz's pioneering and fundamental contributions to these areas. Commemorative articles by those who knew and worked with Samuel Kotz, as well as the detailed exploration of classical and new directions in statistical research, make this volume an essential addition to any statistics library.
| Author | : Seymour Geisser |
| Publisher | : John Wiley & Sons |
| Total Pages | : 218 |
| Release | : 2006-01-27 |
| Genre | : Mathematics |
| ISBN | : 0471743127 |
A fascinating investigation into the foundations of statistical inference This publication examines the distinct philosophical foundations of different statistical modes of parametric inference. Unlike many other texts that focus on methodology and applications, this book focuses on a rather unique combination of theoretical and foundational aspects that underlie the field of statistical inference. Readers gain a deeper understanding of the evolution and underlying logic of each mode as well as each mode's strengths and weaknesses. The book begins with fascinating highlights from the history of statistical inference. Readers are given historical examples of statistical reasoning used to address practical problems that arose throughout the centuries. Next, the book goes on to scrutinize four major modes of statistical inference: * Frequentist * Likelihood * Fiducial * Bayesian The author provides readers with specific examples and counterexamples of situations and datasets where the modes yield both similar and dissimilar results, including a violation of the likelihood principle in which Bayesian and likelihood methods differ from frequentist methods. Each example is followed by a detailed discussion of why the results may have varied from one mode to another, helping the reader to gain a greater understanding of each mode and how it works. Moreover, the author provides considerable mathematical detail on certain points to highlight key aspects of theoretical development. The author's writing style and use of examples make the text clear and engaging. This book is fundamental reading for graduate-level students in statistics as well as anyone with an interest in the foundations of statistics and the principles underlying statistical inference, including students in mathematics and the philosophy of science. Readers with a background in theoretical statistics will find the text both accessible and absorbing.
| Author | : Bovas Abraham |
| Publisher | : John Wiley & Sons |
| Total Pages | : 474 |
| Release | : 2009-09-25 |
| Genre | : Mathematics |
| ISBN | : 0470317299 |
The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "This book, it must be said, lives up to the words on its advertising cover: 'Bridging the gap between introductory, descriptive approaches and highly advanced theoretical treatises, it provides a practical, intermediate level discussion of a variety of forecasting tools, and explains how they relate to one another, both in theory and practice.' It does just that!" -Journal of the Royal Statistical Society "A well-written work that deals with statistical methods and models that can be used to produce short-term forecasts, this book has wide-ranging applications. It could be used in the context of a study of regression, forecasting, and time series analysis by PhD students; or to support a concentration in quantitative methods for MBA students; or as a work in applied statistics for advanced undergraduates." -Choice Statistical Methods for Forecasting is a comprehensive, readable treatment of statistical methods and models used to produce short-term forecasts. The interconnections between the forecasting models and methods are thoroughly explained, and the gap between theory and practice is successfully bridged. Special topics are discussed, such as transfer function modeling; Kalman filtering; state space models; Bayesian forecasting; and methods for forecast evaluation, comparison, and control. The book provides time series, autocorrelation, and partial autocorrelation plots, as well as examples and exercises using real data. Statistical Methods for Forecasting serves as an outstanding textbook for advanced undergraduate and graduate courses in statistics, business, engineering, and the social sciences, as well as a working reference for professionals in business, industry, and government.
| Author | : Jirí Andel |
| Publisher | : John Wiley & Sons |
| Total Pages | : 272 |
| Release | : 2009-09-25 |
| Genre | : Mathematics |
| ISBN | : 0470317914 |
Mathematics of Chance utilizes simple, real-world problems-some of which have only recently been solved-to explain fundamental probability theorems, methods, and statistical reasoning. Jiri Andel begins with a basic introduction to probability theory and its important points before moving on to more specific sections on vital aspects of probability, using both classic and modern problems. Each chapter begins with easy, realistic examples before covering the general formulations and mathematical treatments used. The reader will find ample use for a chapter devoted to matrix games and problem sets concerning waiting, probability calculations, expectation calculations, and statistical methods. A special chapter utilizes problems that relate to areas of mathematics outside of statistics and considers certain mathematical concepts from a probabilistic point of view. Sections and problems cover topics including: * Random walks * Principle of reflection * Probabilistic aspects of records * Geometric distribution * Optimization * The LAD method, and more Knowledge of the basic elements of calculus will be sufficient in understanding most of the material presented here, and little knowledge of pure statistics is required. Jiri Andel has produced a compact reference for applied statisticians working in industry and the social and technical sciences, and a book that suits the needs of students seeking a fundamental understanding of probability theory.
