Nonparametric Statistics for Non-Statisticians, Corder Gregory W
Автор: Corder Название: Nonparametric Statistics - A Step-by-Step Approach 2e ISBN: 1118840313 ISBN-13(EAN): 9781118840313 Издательство: Wiley Цена: 8951 р. Наличие на складе: Есть у поставщикаПоставка под заказ. Описание: a very useful resource for courses in nonparametric statistics in which the emphasis is on applications rather than on theory. It also deserves a place in libraries of all institutions where introductory statistics courses are taught.
Автор: Seber George A F Название: Matrix Handbook for Statisticians ISBN: 0471748692 ISBN-13(EAN): 9780471748694 Издательство: Wiley Рейтинг: Цена: 15131 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Offers a comprehensive, encyclopedic treatment of matrices as they relate to both statistical concepts and methodologies. This book includes references to both the theory behind the methods and the applications of the methods. It also includes topics, such as rank, eigenvalues, determinants, norms, and generalized inverses.
Название: Statistics for Non-Statisticians ISBN: 3662493489 ISBN-13(EAN): 9783662493489 Издательство: Springer Рейтинг: Цена: 4701 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book was written for those who need to know how to collect, analyze and present data. It is meant to be a first course for practitioners, a book for private study or brush-up on statistics, and supplementary reading for general statistics classes. The book is untraditional, both with respect to the choice of topics and the presentation: Topics were determined by what is most useful for practical statistical work, and the presentation is as non-mathematical as possible. The book contains many examples using statistical functions in spreadsheets. In this second edition, new topics have been included e.g. within the area of statistical quality control, in order to make the book even more useful for practitioners working in industry.
Описание: Statistical Thinking for Non–Statisticians in Drug Regulation, Second Edition , is a need–to–know guide to understanding statistical methodology, statistical data and results within drug development and clinical trials. It provides non–statisticians working in the pharmaceutical and medical device industries with an accessible introduction to the knowledge they need when working with statistical information and communicating with statisticians. It covers the statistical aspects of design, conduct, analysis and presentation of data from clinical trials in drug regulation and improves the ability to read, understand and critically appraise statistical methodology in papers and reports. As such, it is directly concerned with the day–to–day practice and the regulatory requirements of drug development and clinical trials. Fully conversant with current regulatory requirements, this second edition includes five new chapters covering Bayesian statistics, adaptive designs, observational studies, methods for safety analysis and monitoring and statistics for diagnosis. Authored by a respected lecturer and consultant to the pharmaceutical industry, Statistical Thinking for Non–Statisticians in Drug Regulation is an ideal guide for physicians, clinical research scientists, managers and associates, data managers, medical writers, regulatory personnel and for all non–statisticians working and learning within the pharmaceutical industry.
Автор: Lange Название: Numerical Analysis for Statisticians ISBN: 0387949798 ISBN-13(EAN): 9780387949796 Издательство: Springer Рейтинг: Цена: 8355 р. Наличие на складе: Поставка под заказ.
Описание: Numerical analysis is the study of computation and its accuracy, stability and often its implementation on a computer. This book focuses on the principles of numerical analysis. It is suitable for those who use statistics to craft their own software and to understand the advantages and disadvantages of different numerical methods.
Описание: Knowledge of matrix algebra is a prerequisite for the areas of linear statistical models and multivariate statistics. Presenting matrix algebra, this book covers the fundamental concepts along with the specialized topics encountered in areas of statistics such as linear statistical models and multivariate analysis.
Описание: Gives an introduction to deconvolution problems in nonparametric statistics. This title focuses on methodology (description of the estimation procedures) and theory (minimax convergence rates). It provides an appendix chapter on further results of Fourier analysis.
Описание: This book introduces several topics related to linear model theory: multivariate linear models, discriminant analysis, principal components, factor analysis, time series in both the frequency and time domains, and spatial data analysis. The second edition adds new material on nonparametric regression, response surface maximization, and longitudinal models. The book provides a unified approach to these disparate subject and serves as a self-contained companion volume to the author's Plane Answers to Complex Questions: The Theory of Linear Models. Ronald Christensen is Professor of Statistics at the University of New Mexico. He is well known for his work on the theory and application of linear models having linear structure. He is the author of numerous technical articles and several books and he is a Fellow of the American Statistical Association and the Institute of Mathematical Statistics. Also Available: Christensen, Ronald. Plane Answers to Complex Questions: The Theory of Linear Models, Second Edition (1996). New York: Springer-Verlag New York, Inc. Christensen, Ronald. Log-Linear Models and Logistic Regression, Second Edition (1997). New York: Springer-Verlag New York, Inc.
Описание: A fundamental problem in statistical analysis is checking how well a particular probability model fits a set of observed data. In many settings, nonparametric
smoothing methods provide a convenient and powerful means of testing model fit. Nonparametric Smoothing and Lack-of-Fit Tests explores the use of smoothing methods in testing the
fit of parametric regression models.
The book reviews many of the existing methods for testing lack-of-fit and also proposes a number of new methods. Both applied and
theoretical aspects of the model checking problems are addressed. As such, the book should be of interest to practitioners of statistics and researchers investigating either lack-of-fit
tests or nonparametric smoothing ideas.
The first four chapters of the book are an introduction to the problem of estimating regression functions by nonparametric smoothers,
primarily those of kernel and Fourier series type. This part of the book could be used as the foundation for a graduate level course on nonparametric function estimation. The
prerequisites for a full appreciation of the book are a modest knowledge of calculus and some familiarity with the basics of mathematical statistics.
The less mathematically
sophisticated reader will find Chapter 2 to be a comprehensible introduction to smoothing ideas and the rest of the book to be a valuable reference for both nonparametric function
estimation and lack-of-fit tests. Jeffrey D. Hart is Pr
fessor of Statistics at Texas A&M University.
He is an associate editor of the Journal of the American Statistical Association, an elected Fellow of the Institute of Mathematical
Statistics, and winner of a distinguished teaching award at Texas A&M University.
Автор: Heyde Название: Statisticians of the Centuries ISBN: 0387953299 ISBN-13(EAN): 9780387953298 Издательство: Springer Рейтинг: Цена: 12539 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Contains 104 biographical articles on eminent contributors to statistical ideas born prior to the 20th Century.
Автор: Shorack Название: Probability for Statisticians ISBN: 0387989536 ISBN-13(EAN): 9780387989532 Издательство: Springer Рейтинг: Цена: 9922 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Probability for Statisticians is intended as a text for a one year graduate course aimed especially at students in statistics. The choice of examples illustrates this
intention clearly. The material to be presented in the classroom constitutes a bit more than half the text, and the choices the author makes at the University of Washington in Seattle are
The rest of the text provides background, offers different routes that could be pursued in the classroom, ad offers additional material that is appropriate for
self-study. Of particular interest is a presentation of the major central limit theorems via Stein's method either prior to or alternative to a characteristic funcion presentation. Additionally,
there is considerable emphasis placed on the quantile function as well as the distribution function.
The bootstrap and trimming are both presented. The martingale coverage
includes coverage of censored data martingales. The text includes measure theoretic preliminaries, from which the authors own course typically includes selected coverage.
The author is a professor of Statistics and adjunct professor of Mathematics at the University of Washington in Seattle. He served as chair of the Department of Statistics 1986-- 1989.
He received his PhD in Statistics from Stanford University.
He is a fellow of the Institute of Mathematical Statistics, and is a former associate editor of the Annals of
Описание: Essentials of Probability Theory for Statisticians provides graduate students with a rigorous treatment of probability theory, with an emphasis on results central to theoretical statistics. It presents classical probability theory motivated with illustrative examples in biostatistics, such as outlier tests, monitoring clinical trials, and using adaptive methods to make design changes based on accumulating data. The authors explain different methods of proofs and show how they are useful for establishing classic probability results. After building a foundation in probability, the text intersperses examples that make seemingly esoteric mathematical constructs more intuitive. These examples elucidate essential elements in definitions and conditions in theorems. In addition, counterexamples further clarify nuances in meaning and expose common fallacies in logic. This text encourages students in statistics and biostatistics to think carefully about probability. It gives them the rigorous foundation necessary to provide valid proofs and avoid paradoxes and nonsensical conclusions.
Автор: Brodsky, E., Darkhovsky, B.S. Название: Nonparametric Methods in Change Point Problems ISBN: 0792321227 ISBN-13(EAN): 9780792321224 Издательство: Springer Рейтинг: Цена: 9926 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume deals with non-parametric methods of change point (disorder) detection in random processes and fields. A systematic account is given of up-to-date developments in this rapidly evolving branch of statistics.
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