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Leading Personalities In Statistical Sciences

Author: Norman L. Johnson
Publisher: John Wiley & Sons
ISBN: 1118150724
Size: 61.93 MB
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A fascinating chronicle of the lives and achievements of the men and women who helped shapethe science of statistics This handsomely illustrated volume will make enthralling reading for scientists, mathematicians, and science history buffs alike. Spanning nearly four centuries, it chronicles the lives and achievements of more than 110 of the most prominent names in theoretical and applied statistics and probability. From Bernoulli to Markov, Poisson to Wiener, you will find intimate profiles of women and men whose work led to significant advances in the areas of statistical inference and theory, probability theory, government and economic statistics, medical and agricultural statistics, and science and engineering. To help readers arrive at a fuller appreciation of the contributions these pioneers made, the authors vividly re-create the times in which they lived while exploring the major intellectual currents that shaped their thinking and propelled their discoveries. Lavishly illustrated with more than 40 authentic photographs and woodcuts * Includes a comprehensive timetable of statistics from the seventeenth century to the present * Features edited chapters written by 75 experts from around the globe * Designed for easy reference, features a unique numbering scheme that matches the subject profiled with his or her particular field of interest

Encyclopedia Of Statistical Sciences

Author:
Publisher: John Wiley & Sons
ISBN: 9780471743750
Size: 49.94 MB
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With the publication of this update installment, the Encyclopedia of Statistical Sciences retains its position as the only cutting-edge reference of choice for those working in statistics, probability theory, biostatistics, quality control, and economics and in applications of statistical methods in sociology, engineering, computer and communication science, biomedicine, psychology, and many other areas.

Encyclopedia Of Statistical Sciences

Author: Samuel Kotz
Publisher: Wiley-Interscience
ISBN:
Size: 76.22 MB
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Encyclopedia of Statistical Sciences is the number one source of information on statistical theory, methods, and applications for researchers and clinicians. This new volume is the second of three updates designed to bring the Encyclopedia in line with new and emerging topics and important advances in statistical science made over the past decade. Each self-contained entry is written by a leader in the field and easily understood by readers with a modest statistical background. In addition to the main selections, which feature fascinating discussions of developments in various branches of the statistical sciences, readers will find a series of shorter entries ranging in subject matter from the lives of pioneers in statistics to updates of earlier articles and reviews of statistical agencies and journals. Up-to-date bibliographies, thorough cross-referencing, and extensive indexing facilitate quick access to specific information and provide an indispensable platform for further study and research With the publication of this update installment, the Encyclopedia of Statistical Sciences retains its position as a cutting-edge reference of choice for those working in statistics, probability theory, biostatistics, quality control, and economics and in applications of statistical methods in sociology, engineering, computer science, biomedicine, psychology, and many other areas

Continuous Multivariate Distributions Models And Applications

Author: Samuel Kotz
Publisher: John Wiley & Sons
ISBN: 0471654035
Size: 48.95 MB
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Continuous Multivariate Distributions, Volume 1, Second Edition provides a remarkably comprehensive, self-contained resource for this critical statistical area. It covers all significant advances that have occurred in the field over the past quarter century in the theory, methodology, inferential procedures, computational and simulational aspects, and applications of continuous multivariate distributions. In-depth coverage includes MV systems of distributions, MV normal, MV exponential, MV extreme value, MV beta, MV gamma, MV logistic, MV Liouville, and MV Pareto distributions, as well as MV natural exponential families, which have grown immensely since the 1970s. Each distribution is presented in its own chapter along with descriptions of real-world applications gleaned from the current literature on continuous multivariate distributions and their applications.

Statistics For The Social Sciences

Author: R. Mark Sirkin
Publisher: SAGE
ISBN: 9781412905466
Size: 49.66 MB
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Popular in previous editions, this Third Edition continues to help build students' confidence and ability in doing statistical analysis by slowly moving from concepts that require little computational work to those that require more. Author R. Mark Sirkin once again demonstrates how statistics can be used so that students come to appreciate their usefulness rather than fear them. Statistics for the Social Sciences emphasizes the analysis and interpretation of data to give students a feel for how data interpretation is related to the methods by which the information was obtained.

The Subjectivity Of Scientists And The Bayesian Approach

Author: S. James Press
Publisher: John Wiley & Sons
ISBN: 1118150627
Size: 42.67 MB
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Comparing and contrasting the reality of subjectivity in the work of history's great scientists and the modern Bayesian approach to statistical analysis Scientists and researchers are taught to analyze their data from an objective point of view, allowing the data to speak for themselves rather than assigning them meaning based on expectations or opinions. But scientists have never behaved fully objectively. Throughout history, some of our greatest scientific minds have relied on intuition, hunches, and personal beliefs to make sense of empirical data-and these subjective influences have often aided in humanity's greatest scientific achievements. The authors argue that subjectivity has not only played a significant role in the advancement of science, but that science will advance more rapidly if the modern methods of Bayesian statistical analysis replace some of the classical twentieth-century methods that have traditionally been taught. To accomplish this goal, the authors examine the lives and work of history's great scientists and show that even the most successful have sometimes misrepresented findings or been influenced by their own preconceived notions of religion, metaphysics, and the occult, or the personal beliefs of their mentors. Contrary to popular belief, our greatest scientific thinkers approached their data with a combination of subjectivity and empiricism, and thus informally achieved what is more formally accomplished by the modern Bayesian approach to data analysis. Yet we are still taught that science is purely objective. This innovative book dispels that myth using historical accounts and biographical sketches of more than a dozen great scientists, including Aristotle, Galileo Galilei, Johannes Kepler, William Harvey, Sir Isaac Newton, Antoine Levoisier, Alexander von Humboldt, Michael Faraday, Charles Darwin, Louis Pasteur, Gregor Mendel, Sigmund Freud, Marie Curie, Robert Millikan, Albert Einstein, Sir Cyril Burt, and Margaret Mead. Also included is a detailed treatment of the modern Bayesian approach to data analysis. Up-to-date references to the Bayesian theoretical and applied literature, as well as reference lists of the primary sources of the principal works of all the scientists discussed, round out this comprehensive treatment of the subject. Readers will benefit from this cogent and enlightening view of the history of subjectivity in science and the authors' alternative vision of how the Bayesian approach should be used to further the cause of science and learning well into the twenty-first century.

Comparative Statistical Inference

Author: Vic Barnett
Publisher: John Wiley & Sons
ISBN: 9780471976431
Size: 50.39 MB
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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.

Statistical Tests For Mixed Linear Models

Author: André I. Khuri
Publisher: John Wiley & Sons
ISBN: 1118164857
Size: 51.45 MB
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An advanced discussion of linear models with mixed or random effects. In recent years a breakthrough has occurred in our ability to draw inferences from exact and optimum tests of variance component models, generating much research activity that relies on linear models with mixed and random effects. This volume covers the most important research of the past decade as well as the latest developments in hypothesis testing. It compiles all currently available results in the area of exact and optimum tests for variance component models and offers the only comprehensive treatment for these models at an advanced level. Statistical Tests for Mixed Linear Models: Combines analysis and testing in one self-contained volume. Describes analysis of variance (ANOVA) procedures in balanced and unbalanced data situations. Examines methods for determining the effect of imbalance on data analysis. Explains exact and optimum tests and methods for their derivation. Summarizes test procedures for multivariate mixed and random models. Enables novice readers to skip the derivations and discussions on optimum tests. Offers plentiful examples and exercises, many of which are numerical in flavor. Provides solutions to selected exercises. Statistical Tests for Mixed Linear Models is an accessible reference for researchers in analysis of variance, experimental design, variance component analysis, and linear mixed models. It is also an important text for graduate students interested in mixed models.

Statistical Modeling By Wavelets

Author: Brani Vidakovic
Publisher: John Wiley & Sons
ISBN: 0470317868
Size: 11.83 MB
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A comprehensive, step-by-step introduction to wavelets in statistics. What are wavelets? What makes them increasingly indispensable in statistical nonparametrics? Why are they suitable for "time-scale" applications? How are they used to solve such problems as denoising, regression, or density estimation? Where can one find up-to-date information on these newly "discovered" mathematical objects? These are some of the questions Brani Vidakovic answers in Statistical Modeling by Wavelets. Providing a much-needed introduction to the latest tools afforded statisticians by wavelet theory, Vidakovic compiles, organizes, and explains in depth research data previously available only in disparate journal articles. He carefully balances both statistical and mathematical techniques, supplementing the material with a wealth of examples, more than 100 illustrations, and extensive references-with data sets and S-Plus wavelet overviews made available for downloading over the Internet. Both introductory and data-oriented modeling topics are featured, including: * Continuous and discrete wavelet transformations. * Statistical optimality properties of wavelet shrinkage. * Theoretical aspects of wavelet density estimation. * Bayesian modeling in the wavelet domain. * Properties of wavelet-based random functions and densities. * Several novel and important wavelet applications in statistics. * Wavelet methods in time series. Accessible to anyone with a background in advanced calculus and algebra, Statistical Modeling by Wavelets promises to become the standard reference for statisticians and engineers seeking a comprehensive introduction to an emerging field.

Mathematics Of Chance

Author: Jirí Andel
Publisher: John Wiley & Sons
ISBN: 0470317914
Size: 77.16 MB
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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.