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Probability and Statistical Inference 8 ed.



¬арианты приобретени€
÷ена: 4208р.
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Ќаличие: ќтсутствует. ¬озможна поставка под заказ.

ѕри оформлении заказа до: 21 фев 2020
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јвтор: Elliot Tanis Robert Hogg &
Ќазвание:  Probability and Statistical Inference 8 ed.   (–оберт “анис: ¬еро€тность и статистическое взаимодействие)
»здательство: Pearson Education
 лассификаци€:
¬еро€тность и статистика

ISBN: 129202478X
ISBN-13(EAN): 9781292024783
ISBN: 1-292-02478-X
ISBN-13(EAN): 978-1-292-02478-3
ќбложка/‘ормат: Hardcover
ƒата издани€: 23.07.2013
–азмер: 230 X 193 X 34
ѕоставл€етс€ из: —Ўј



      —тарое издание
Probability and Statistical Inference: United States Edition

јвтор: Robert Hogg
Ќазвание: Probability and Statistical Inference: United States Edition
ISBN: 0131464132 ISBN-13(EAN): 9780131464131
»здательство: Pearson Education
÷ена: 3717 р.
Ќаличие на складе: Ќевозможна поставка.
ќписание: This applied introduction to the mathematics of probability and statistics emphasizes the existence of variation in almost every process, and how the study of probability and statistics helps us understand this variability. Designed for students with a background in calculus, it reinforces basic mathematical concepts with numerous real-world examples and applications to illustrate the relevance of key concepts.

Probability and Statistical Inference: United States Edition 8 Book cased plus CD - 1 ISBN

јвтор: Robert Hogg
Ќазвание: Probability and Statistical Inference: United States Edition 8 Book cased plus CD - 1 ISBN
ISBN: 0321584759 ISBN-13(EAN): 9780321584755
»здательство: Pearson Education
÷ена: 3717 р.
Ќаличие на складе: Ќевозможна поставка.

Probability and Statistical Inference

јвтор: Hogg Robert
Ќазвание: Probability and Statistical Inference
ISBN: 032163635X ISBN-13(EAN): 9780321636355
»здательство: Pearson Education
÷ена: 3717 р.
Ќаличие на складе: Ќевозможна поставка.

Probability and Statistical Inference, Global Edition

јвтор: Robert Hogg Elliot Tanis
Ќазвание: Probability and Statistical Inference, Global Edition
ISBN: 1292062355 ISBN-13(EAN): 9781292062358
»здательство: Pearson Education
÷ена: 4208 р.
Ќаличие на складе: ѕоставка под заказ.
ќписание: For a one- or two-semester course; calculus background presumed, no previous study of probability or statistics is required. Written by three veteran statisticians, this applied introduction to probability and statistics emphasizes the existence of variation in almost every process, and how the study of probability and statistics helps us understand this variation. Designed for students with a background in calculus, this book continues to reinforce basic mathematical concepts with numerous real-world examples and applications to illustrate the relevance of key concepts.



Causal Inference for Statistics, Social, and Biomedical Sciences

јвтор: Imbens
Ќазвание: Causal Inference for Statistics, Social, and Biomedical Sciences
ISBN: 0521885884 ISBN-13(EAN): 9780521885881
»здательство: Cambridge Academ
–ейтинг:
÷ена: 4683 р.
Ќаличие на складе: ≈сть у поставщика ѕоставка под заказ.

ќписание: Most questions in social and biomedical sciences are causal in nature: what would happen to individuals, or to groups, if part of their environment were changed? In this groundbreaking text, two world-renowned experts present statistical methods for studying such questions. This book starts with the notion of potential outcomes, each corresponding to the outcome that would be realized if a subject were exposed to a particular treatment or regime. In this approach, causal effects are comparisons of such potential outcomes. The fundamental problem of causal inference is that we can only observe one of the potential outcomes for a particular subject. The authors discuss how randomized experiments allow us to assess causal effects and then turn to observational studies. They lay out the assumptions needed for causal inference and describe the leading analysis methods, including matching, propensity-score methods, and instrumental variables. Many detailed applications are included, with special focus on practical aspects for the empirical researcher.

Introductory Statistical Inference

јвтор: Mukhopadhyay, Nitis
Ќазвание: Introductory Statistical Inference
ISBN: 1574446134 ISBN-13(EAN): 9781574446135
»здательство: Taylor&Francis
–ейтинг:
÷ена: 9195 р.
Ќаличие на складе: Ќевозможна поставка.

ќписание: This gracefully organized text reveals the rigorous theory of probability and statistical inference in the style of a tutorial, using worked examples, exercises, figures, tables, and computer simulations to develop and illustrate concepts. Drills and boxed summaries emphasize and reinforce important ideas and special techniques. Beginning with a review of the basic concepts and methods in probability theory, moments, and moment generating functions, the author moves to more intricate topics.

"Introductory Statistical Inference" studies multivariate random variables, exponential families of distributions, and standard probability inequalities. It develops the Helmert transformation for normal distributions, introduces the notions of convergence, and spotlights the central limit theorems.In this text, coverage highlights sampling distributions, Basu's theorem, Rao-Blackwellization and the Cramer-Rao inequality. The text also provides in-depth coverage of Lehmann-Scheffe theorems, focuses on tests of hypotheses, describes Bayesian methods and the Bayes' estimator, and develops large-sample inference.

The author provides a historical context for statistics and statistical discoveries and answers to a majority of the end-of-chapter exercises. Designed primarily for a one-semester, first-year graduate course in probability and statistical inference, this text serves readers from varied backgrounds, ranging from engineering, economics, agriculture, and bioscience to finance, financial mathematics, operations and information management, and psychology.

Foundations of Statistical Inference / Proceedings of the Shoresh Conference 2000

јвтор: Haitovsky Yoel, Lerche Hans Rudolf, Ritov Yaacov
Ќазвание: Foundations of Statistical Inference / Proceedings of the Shoresh Conference 2000
ISBN: 3790800473 ISBN-13(EAN): 9783790800470
»здательство: Springer
–ейтинг:
÷ена: 8882 р.
Ќаличие на складе: ≈сть у поставщика ѕоставка под заказ.

ќписание: This volume is a compressed survey containing recent results on statistics of stochastic processes and on identification with incomplete observations. It comprises a collection of papers presented at the Shoresh Conference 2000 on the Foundation of Statistical Inference. The papers cover the following areas with high research activity:- Identification with Incomplete Observations, Data Mining,- Bayesian Methods and Modelling,- Testing, Goodness of Fit and Randomness,- Statistics of Stationary Processes.

Statistical and Inductive Inference by Minimum Message Length

јвтор: Wallace
Ќазвание: Statistical and Inductive Inference by Minimum Message Length
ISBN: 038723795X ISBN-13(EAN): 9780387237954
»здательство: Springer
–ейтинг:
÷ена: 14492 р.
Ќаличие на складе: ≈сть у поставщика ѕоставка под заказ.

ќписание: The Minimum Message Length (MML) Principle is an information-theoretic approach to induction, hypothesis testing, model selection, and statistical inference. MML, which provides a formal specification for the implementation of Occam's Razor, asserts that the вАШbestвАЩ explanation of observed data is the shortest. Further, an explanation is acceptable (i.e. the induction is justified) only if the explanation is shorter than the original data.This book gives a sound introduction to the Minimum Message Length Principle and its applications, provides the theoretical arguments for the adoption of the principle, and shows the development of certain approximations that assist its practical application. MML appears also to provide both a normative and a descriptive basis for inductive reasoning generally, and scientific induction in particular. The book describes this basis and aims to show its relevance to the Philosophy of Science.Statistical and Inductive Inference by Minimum Message Length will be of special interest to graduate students and researchers in Machine Learning and Data Mining, scientists and analysts in various disciplines wishing to make use of computer techniques for hypothesis discovery, statisticians and econometricians interested in the underlying theory of their discipline, and persons interested in the Philosophy of Science. The book could also be used in a graduate-level course in Machine Learning and Estimation and Model-selection, Econometrics and Data Mining."Any statistician interested in the foundations of the discipline, or the deeper philosophical issues of inference, will find this volume a rewarding read." Short Book Reviews of the International Statistical Institute,  December 2005

јвтор: Sunil K. Mathur
Ќазвание: Probability and Statistical Inference Using R,
ISBN: 012386982X ISBN-13(EAN): 9780123869821
»здательство: Elsevier Science
÷ена: 6634 р.
Ќаличие на складе: Ќевозможна поставка.

Constrained Statistical Inference: Order, Inequality, and Shape Constraints

јвтор: Mervyn J. Silvapulle
Ќазвание: Constrained Statistical Inference: Order, Inequality, and Shape Constraints
ISBN: 0471208272 ISBN-13(EAN): 9780471208273
»здательство: Wiley
–ейтинг:
÷ена: 14003 р.
Ќаличие на складе: ≈сть у поставщика ѕоставка под заказ.

ќписание: This volumes focuses on the theory of statistical inference under inequality constraints, providing a unified and up-to-date treatment of the methodology. The scope of applications of the presented methodology and theory in different fields is clearly illustrated by using examples from several areas, especially sociology, econometrics,d biostatistics. The authors also discuss a broad range of other inequality constrained inference problems, which do not fit well in the contemplated unified framework, providing meaningful access to comprehend methodological resolutions.

A History of Parametric Statistical Inference from Bernoulli to Fisher, 1713-1935

јвтор: Hald Anders
Ќазвание: A History of Parametric Statistical Inference from Bernoulli to Fisher, 1713-1935
ISBN: 0387464085 ISBN-13(EAN): 9780387464084
»здательство: Springer
–ейтинг:
÷ена: 10284 р.
Ќаличие на складе: ≈сть у поставщика ѕоставка под заказ.

ќписание: This is a history of parametric statistical inference, written by one of the most important historians of statistics of the 20th century, Anders Hald. This book can be viewed as a follow-up to his two most recent books, although this current text is much more streamlined and contains new analysis of many ideas and developments. And unlike his other books, which were encyclopedic by nature, this book can be used for a course on the topic, the only prerequisites being a basic course in probability and statistics.The book is divided into five main sections:* Binomial statistical inference;* Statistical inference by inverse probability;* The central limit theorem and linear minimum variance estimation by Laplace and Gauss;* Error theory, skew distributions, correlation, sampling distributions;* The Fisherian Revolution, 1912-1935.Throughout each of the chapters, the author provides lively biographical sketches of many of the main characters, including Laplace, Gauss, Edgeworth, Fisher, and Karl Pearson. He also examines the roles played by DeMoivre, James Bernoulli, and Lagrange, and he provides an accessible exposition of the work of R.A. Fisher.This book will be of interest to statisticians, mathematicians, undergraduate and graduate students, and historians of science.

Statistical Inference for Ergodic Diffusion Processes

јвтор: Kutoyants Yury A.
Ќазвание: Statistical Inference for Ergodic Diffusion Processes
ISBN: 1852337591 ISBN-13(EAN): 9781852337599
»здательство: Springer
–ейтинг:
÷ена: 14492 р.
Ќаличие на складе: ≈сть у поставщика ѕоставка под заказ.

ќписание: Statistical Inference for Ergodic Diffusion Processes encompasses a wealth of results from over ten years of mathematical literature. It provides a comprehensive overview of existing techniques, and presents - for the first time in book form - many new techniques and approaches. An elementary introduction to the field at the start of the book introduces a class of examples - both non-standard and classical - that reappear as the investigation progresses to illustrate the merits and demerits of the procedures. The statements of the problems are in the spirit of classical mathematical statistics, and special attention is paid to asymptotically efficient procedures. Today, diffusion processes are widely used in applied problems in fields such as physics, mechanics and, in particular, financial mathematics. This book provides a state-of-the-art reference that will prove invaluable to researchers, and graduate and postgraduate students, in areas such as financial mathematics, economics, physics, mechanics and the biomedical sciences.From the reviews:"This book is very much in the Springer mould of graduate mathematical statistics books, giving rapid access to the latest literature...It presents a strong discussion of nonparametric and semiparametric results, from both classical and Bayesian standpoints...I have no doubt that it will come to be regarded as a classic text." Journal of the Royal Statistical Society, Series A, v. 167

Principles of Statistical Inference

јвтор: D. R. Cox
Ќазвание: Principles of Statistical Inference
ISBN: 0521685672 ISBN-13(EAN): 9780521685672
»здательство: Cambridge Academ
–ейтинг:
÷ена: 3642 р.
Ќаличие на складе: ≈сть у поставщика ѕоставка под заказ.

ќписание: In this definitive book, D. R. Cox gives a comprehensive and balanced appraisal of statistical inference. He develops the key concepts, describing and comparing the main ideas and controversies over foundational issues that have been keenly argued for more than two-hundred years. Continuing a sixty-year career of major contributions to statistical thought, no one is better placed to give this much-needed account of the field. An appendix gives a more personal assessment of the merits of different ideas. The content ranges from the traditional to the contemporary. While specific applications are not treated, the book is strongly motivated by applications across the sciences and associated technologies. The mathematics is kept as elementary as feasible, though previous knowledge of statistics is assumed. The book will be valued by every user or student of statistics who is serious about understanding the uncertainty inherent in conclusions from statistical analyses.

Essentials of Statistical Inference

јвтор: G. A. Young
Ќазвание: Essentials of Statistical Inference
ISBN: 0521839718 ISBN-13(EAN): 9780521839716
»здательство: Cambridge Academ
–ейтинг:
÷ена: 7597 р.
Ќаличие на складе: ≈сть у поставщика ѕоставка под заказ.

ќписание: This engaging textbook presents the concepts and results underlying the Bayesian, frequentist and Fisherian approaches to statistical inference, with particular emphasis on the contrasts between them. Aimed at advanced undergraduates and graduate students in mathematics and related disciplines, it covers in a concise treatment both basic mathematical theory and more advanced material, including such contemporary topics as Bayesian computation, higher-order likelihood theory, predictive inference, bootstrap methods and conditional inference. It contains numerous extended examples of the application of formal inference techniques to real data, as well as historical commentary on the development of the subject. Throughout, the text concentrates on concepts, rather than mathematical detail, while maintaining appropriate levels of formality. Each chapter ends with a set of accessible problems. Some prior knowledge of probability is assumed, while some previous knowledge of the objectives and main approaches to statistical inference would be helpful but is not essential.

Advances in statistical modeling and inference: essays in honor of kjell a doksum

Ќазвание: Advances in statistical modeling and inference: essays in honor of kjell a doksum
ISBN: 9812703691 ISBN-13(EAN): 9789812703699
»здательство: World Scientific Publishing
–ейтинг:
÷ена: 30357 р.
Ќаличие на складе: ѕоставка под заказ.

ќписание: There have been major developments in the field of statistics over the last quarter century, spurred by the rapid advances in computing and data-measurement technologies. These developments have revolutionized the field and have greatly influenced research directions in theory and methodology. Increased computing power has spawned entirely new areas of research in computationally-intensive methods, allowing us to move away from narrowly applicable parametric techniques based on restrictive assumptions to much more flexible and realistic models and methods.

These computational advances have also led to the extensive use of simulation and Monte Carlo techniques in statistical inference. All of these developments have, in turn, stimulated new research in theoretical statistics. This volume provides an up-to-date overview of recent advances in statistical modeling and inference.

Written by renowned researchers from across the world, it discusses flexible models, semi-parametric methods and transformation models, nonparametric regression and mixture models, survival and reliability analysis, and re-sampling techniques. With its coverage of methodology and theory as well as applications, the book is an essential reference for researchers, graduate students, and practitioners.

Essential Statistical Inference

јвтор: Boos
Ќазвание: Essential Statistical Inference
ISBN: 1461448174 ISBN-13(EAN): 9781461448174
»здательство: Springer
–ейтинг:
÷ена: 9349 р.
Ќаличие на складе: ≈сть у поставщика ѕоставка под заказ.

ќписание: A superb resource on statistical inference for researchers or students, this book has R code throughout, including in sample problems, and an appendix of derived notation and formulae. It covers core topics as well as modern aspects such as M-estimation.


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