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Группа авторов Sampling Statistics - volgomoda.ru
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Группа авторов Handbook of U.S. Labor Statistics 2020

Группа авторов Survey Sampling in Economic and Social Research. SE 120

Группа авторов Sampling Statistics


Discover the latest developments and current practices in survey sampling Survey sampling is an important component of research in many fields, and as the importance of survey sampling continues to grow, sophisticated sampling techniques that are both economical and scientifically reliable are essential to planning statistical research and the design of experiments. Sampling Statistics presents estimation techniques and sampling concepts to facilitate the application of model-based procedures to survey samples. The book begins with an introduction to standard probability sampling concepts, which provides the foundation for studying samples selected from a finite population. The development of the theory of complex sampling methods is detailed, and subsequent chapters explore the construction of estimators, sample design, replication variance estimation, and procedures such as nonresponse adjustment and small area estimation where models play a key role. A final chapter covers analytic studies in which survey data are used for the estimation of parameters for a subject matter model. The author draws upon his extensive experience with survey samples in the book's numerous examples. Both the production of «general use» databases and the analytic study of a limited number of characteristics are discussed. Exercises at the end of each chapter allow readers to test their comprehension of the presented concepts and techniques, and the references provide further resources for study. Sampling Statistics is an ideal book for courses in survey sampling at the graduate level. It is also a valuable reference for practicing statisticians who analyze survey data or are involved in the design of sample surveys.

12503.82 RUR

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Группа авторов Vital Statistics of the United States 2020

Группа авторов Fundamentals of Environmental Sampling and Analysis


An integrated approach to understanding the principles of sampling, chemical analysis, and instrumentation This unique reference focuses on the overall framework and why various methodologies are used in environmental sampling and analysis. An understanding of the underlying theories and principles empowers environmental professionals to select and adapt the proper sampling and analytical protocols for specific contaminants as well as for specific project applications. Covering both field sampling and laboratory analysis, Fundamentals of Environmental Sampling and Analysis includes: A review of the basic analytical and organic chemistry, statistics, hydrogeology, and environmental regulations relevant to sampling and analysis An overview of the fundamentals of environmental sampling design, sampling techniques, and quality assurance/quality control (QA/QC) essential to acquire quality environmental data A detailed discussion of: the theories of absorption spectroscopy for qualitative and quantitative environmental analysis; metal analysis using various atomic absorption and emission spectrometric methods; and the instrumental principles of common chromatographic and electrochemical methods An introduction to advanced analytical techniques, including various hyphenated mass spectrometries and nuclear magnetic resonance spectroscopy With real-life case studies that illustrate the principles plus problems and questions at the end of each chapter to solidify understanding, this is a practical, hands-on reference for practitioners and a great textbook for upper-level undergraduates and graduate students in environmental science and engineering.

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Группа авторов A Probability and Statistics Companion


An accessible and engaging introduction to the study of probability and statistics Utilizing entertaining real-world examples, A Probability and Statistics Companion provides aunique, interesting, and accessible introduction to probability and statistics. This one-of-a-kind book delves into practical topics that are crucial in the analysis of sample surveys and experimentation. This handy book contains introductory explanations of the major topics in probability and statistics, including hypothesis testing and regression, while also delving into more advanced topics such as the analysis of sample surveys, analysis of experimental data, and statistical process control. The book recognizes that there are many sampling techniques that can actually improve on simple random sampling, and in addition, an introduction to the design of experiments is provided to reflect recent advances in conducting scientific experiments. This blend of coverage results in the development of a deeper understanding and solid foundation for the study of probability and statistics. Additional topical coverage includes: Probability and sample spaces Choosing the best candidate Acceptance sampling Conditional probability Random variables and discrete probability distributions Waiting time problems Continuous probability distributions Statistical inference Nonparametric methods Least squares and medians Recursions and probability Each chapter contains exercises and explorations for readers who wish to conduct independent projects or investigations. The discussion of most methods is complemented with applications to engaging, real-world scenarios such as winning speeds at the Indianapolis 500 and predicting winners of the World Series. In addition, the book enhances the visual nature of the subject with numerous multidimensional graphical representations of the presented examples. A Probability and Statistics Companion is an excellent book for introductory probability and statistics courses at the undergraduate level. It is also a valuable reference for professionals who use statistical concepts to make informed decisions in their day-to-day work.

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Yves Tille Sampling and Estimation from Finite Populations


A much-needed reference on survey sampling and its applications that presents the latest advances in the field Seeking to show that sampling theory is a living discipline with a very broad scope, this book examines the modern development of the theory of survey sampling and the foundations of survey sampling. It offers readers a critical approach to the subject and discusses putting theory into practice. It also explores the treatment of non-sampling errors featuring a range of topics from the problems of coverage to the treatment of non-response. In addition, the book includes real examples, applications, and a large set of exercises with solutions. Sampling and Estimation from Finite Populations begins with a look at the history of survey sampling. It then offers chapters on: population, sample, and estimation; simple and systematic designs; stratification; sampling with unequal probabilities; balanced sampling; cluster and two-stage sampling; and other topics on sampling, such as spatial sampling, coordination in repeated surveys, and multiple survey frames. The book also includes sections on: post-stratification and calibration on marginal totals; calibration estimation; estimation of complex parameters; variance estimation by linearization; and much more. Provides an up-to-date review of the theory of sampling Discusses the foundation of inference in survey sampling, in particular, the model-based and design-based frameworks Reviews the problems of application of the theory into practice Also deals with the treatment of non sampling errors Sampling and Estimation from Finite Populations is an excellent book for methodologists and researchers in survey agencies and advanced undergraduate and graduate students in social science, statistics, and survey courses.

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Группа авторов Advanced Calculus with Applications in Statistics


Designed to help motivate the learning of advanced calculus by demonstrating its relevance in the field of statistics, this successful text features detailed coverage of optimization techniques and their applications in statistics while introducing the reader to approximation theory. The Second Edition provides substantial new coverage of the material, including three new chapters and a large appendix that contains solutions to almost all of the exercises in the book. Applications of some of these methods in statistics are discusses.

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Группа авторов Approximation Theorems of Mathematical Statistics


Approximation Theorems of Mathematical Statistics This convenient paperback edition makes a seminal text in statistics accessible to a new generation of students and practitioners. Approximation Theorems of Mathematical Statistics covers a broad range of limit theorems useful in mathematical statistics, along with methods of proof and techniques of application. The manipulation of «probability» theorems to obtain «statistical» theorems is emphasized. Besides a knowledge of these basic statistical theorems, this lucid introduction to the subject imparts an appreciation of the instrumental role of probability theory. The book makes accessible to students and practicing professionals in statistics, general mathematics, operations research, and engineering the essentials of: * The tools and foundations that are basic to asymptotic theory in statistics * The asymptotics of statistics computed from a sample, including transformations of vectors of more basic statistics, with emphasis on asymptotic distribution theory and strong convergence * Important special classes of statistics, such as maximum likelihood estimates and other asymptotic efficient procedures; W. Hoeffding's U-statistics and R. von Mises's «differentiable statistical functions» * Statistics obtained as solutions of equations («M-estimates»), linear functions of order statistics («L-statistics»), and rank statistics («R-statistics») * Use of influence curves * Approaches toward asymptotic relative efficiency of statistical test procedures

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Группа авторов Stage-Wise Adaptive Designs


An expert introduction to stage-wise adaptive designs in all areas of statistics Stage-Wise Adaptive Designs presents the theory and methodology of stage-wise adaptive design across various areas of study within the field of statistics, from sampling surveys and time series analysis to generalized linear models and decision theory. Providing the necessary background material along with illustrative S-PLUS functions, this book serves as a valuable introduction to the problems of adaptive designs. The author begins with a cohesive introduction to the subject and goes on to concentrate on generalized linear models, followed by stage-wise sampling procedures in sampling surveys. Adaptive forecasting in the area of time series analysis is presented in detail, and two chapters are devoted to applications in clinical trials. Bandits problems are also given a thorough treatment along with sequential detection of change-points, sequential applications in industrial statistics, and software reliability. S-Plus functions are available to accompany particular computations, and all examples can be worked out using R, which is available on the book's related FTP site. In addition, a detailed appendix outlines the use of these software functions, while an extensive bibliography directs readers to further research on the subject matter. Assuming only a basic background in statistical topics, Stage-Wise Adaptive Designs is an excellent supplement to statistics courses at the upper-undergraduate and graduate levels. It also serves as a valuable reference for researchers and practitioners in the fields of statistics and biostatistics.

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Peter Lee M. Bayesian Statistics. An Introduction


Bayesian Statistics is the school of thought that combines prior beliefs with the likelihood of a hypothesis to arrive at posterior beliefs. The first edition of Peter Lee’s book appeared in 1989, but the subject has moved ever onwards, with increasing emphasis on Monte Carlo based techniques. This new fourth edition looks at recent techniques such as variational methods, Bayesian importance sampling, approximate Bayesian computation and Reversible Jump Markov Chain Monte Carlo (RJMCMC), providing a concise account of the way in which the Bayesian approach to statistics develops as well as how it contrasts with the conventional approach. The theory is built up step by step, and important notions such as sufficiency are brought out of a discussion of the salient features of specific examples. This edition: Includes expanded coverage of Gibbs sampling, including more numerical examples and treatments of OpenBUGS, R2WinBUGS and R2OpenBUGS. Presents significant new material on recent techniques such as Bayesian importance sampling, variational Bayes, Approximate Bayesian Computation (ABC) and Reversible Jump Markov Chain Monte Carlo (RJMCMC). Provides extensive examples throughout the book to complement the theory presented. Accompanied by a supporting website featuring new material and solutions. More and more students are realizing that they need to learn Bayesian statistics to meet their academic and professional goals. This book is best suited for use as a main text in courses on Bayesian statistics for third and fourth year undergraduates and postgraduate students.

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Steven Thompson K. Sampling


Praise for the Second Edition «This book has never had a competitor. It is the only book that takes a broad approach to sampling . . . any good personal statistics library should include a copy of this book.» —Technometrics «Well-written . . . an excellent book on an important subject. Highly recommended.» —Choice «An ideal reference for scientific researchers and other professionals who use sampling.» —Zentralblatt Math Features new developments in the field combined with all aspects of obtaining, interpreting, and using sample data Sampling provides an up-to-date treatment of both classical and modern sampling design and estimation methods, along with sampling methods for rare, clustered, and hard-to-detect populations. This Third Edition retains the general organization of the two previous editions, but incorporates extensive new material—sections, exercises, and examples—throughout. Inside, readers will find all-new approaches to explain the various techniques in the book; new figures to assist in better visualizing and comprehending underlying concepts such as the different sampling strategies; computing notes for sample selection, calculation of estimates, and simulations; and more. Organized into six sections, the book covers basic sampling, from simple random to unequal probability sampling; the use of auxiliary data with ratio and regression estimation; sufficient data, model, and design in practical sampling; useful designs such as stratified, cluster and systematic, multistage, double and network sampling; detectability methods for elusive populations; spatial sampling; and adaptive sampling designs. Featuring a broad range of topics, Sampling, Third Edition serves as a valuable reference on useful sampling and estimation methods for researchers in various fields of study, including biostatistics, ecology, and the health sciences. The book is also ideal for courses on statistical sampling at the upper-undergraduate and graduate levels.

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Группа авторов Subjective and Objective Bayesian Statistics


Shorter, more concise chapters provide flexible coverage of the subject. Expanded coverage includes: uncertainty and randomness, prior distributions, predictivism, estimation, analysis of variance, and classification and imaging. Includes topics not covered in other books, such as the de Finetti Transform. Author S. James Press is the modern guru of Bayesian statistics.

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Группа авторов Multiple Time Series


The Wiley Series in Probability and Statistics is a collection of topics of current research interests in both pure and applied statistics and probability developments in the field and classical methods. This series provides essential and invaluable reading for all statisticians, whether in academia, industry, government, or research.

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Группа авторов Agricultural Survey Methods


Due to the widespread use of surveys in agricultural resources estimation there is a broad and recognizable interest in methods and techniques to collect and process agricultural data. This book brings together the knowledge of academics and experts to increase the dissemination of the latest developments in agricultural statistics. Conducting a census, setting up frames and registers and using administrative data for statistical purposes are covered and issues arising from sample design and estimation, use of remote sensing, management of data quality and dissemination and analysis of survey data are explored. Key features: Brings together high quality research on agricultural statistics from experts in this field. Provides a thorough and much needed overview of developments within agricultural statistics. Contains summaries for each chapter, providing a valuable reference framework for those new to the field. Based upon a selection of key methodological papers presented at the ICAS conference series, updated and expanded to address current issues. Covers traditional statistical methodologies including sampling and weighting. This book provides a much needed guide to conducting surveys of land use and to the latest developments in agricultural statistics. Statisticians interested in agricultural statistics, agricultural statisticians in national statistics offices and statisticians and researchers using survey methodology will benefit from this book.

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Группа авторов A Guide to Business Statistics


An accessible text that explains fundamental concepts in business statistics that are often obscured by formulae and mathematical notation A Guide to Business Statistics offers a practical approach to statistics that covers the fundamental concepts in business and economics. The book maintains the level of rigor of a more conventional textbook in business statistics but uses a more stream­lined and intuitive approach. In short, A Guide to Business Statistics provides clarity to the typical statistics textbook cluttered with notation and formulae. The author—an expert in the field—offers concise and straightforward explanations to the core principles and techniques in business statistics. The concepts are intro­duced through examples, and the text is designed to be accessible to readers with a variety of backgrounds. To enhance learning, most of the mathematical formulae and notation appears in technical appendices at the end of each chapter. This important resource: • Offers a comprehensive guide to understanding business statistics targeting business and economics students and professionals • Introduces the concepts and techniques through concise and intuitive examples • Focuses on understanding by moving distracting formulae and mathematical notation to appendices • Offers intuition, insights, humor, and practical advice for students of business statistics • Features coverage of sampling techniques, descriptive statistics, probability, sampling distributions, confidence intervals, hypothesis tests, and regression Written for undergraduate business students, business and economics majors, teachers, and practitioners, A Guide to Business Statistics offers an accessible guide to the key concepts and fundamental principles in statistics. DAVID M. McEVOY, PhD, is an Associate Professor in the Economics Department at Appalachian State University in Boone NC. He has published over 20 peer-reviewed articles and is coeditor of two books. Dr. McEvoy is an award-winning educator who has taught undergraduate courses in business statistics for over 10 years. DAVID M. McEVOY, PhD, is an Associate Professor in the Economics Department at Appalachian State University in Boone NC. He has published over 20 peer-reviewed articles and is coeditor of two books. Dr. McEvoy is an award-winning educator who has taught undergraduate courses in business statistics for over 10 years.An accessible text that explains fundamental conceptsin business statistics that are often obscured by formulae and mathematical notationA Guide to Business Statistics offers a practical approach to statistics that covers the fundamental concepts in business and economics. The book maintains the level of rigor of a more conventional textbook in business statistics but uses a more streamlined and intuitive approach. In short, A Guide to Business Statistics provides clarity to the typical statistics textbook cluttered with notation and formulae.The author—an expert in the field—offers concise and straightforward explanations to the core principles and techniques in business statistics. The concepts are introduced through examples, and the text is designed to be accessible

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Hesterberg Tim C. Mathematical Statistics with Resampling and R


This book bridges the latest software applications with the benefits of modern resampling techniques Resampling helps students understand the meaning of sampling distributions, sampling variability, P-values, hypothesis tests, and confidence intervals. This groundbreaking book shows how to apply modern resampling techniques to mathematical statistics. Extensively class-tested to ensure an accessible presentation, Mathematical Statistics with Resampling and R utilizes the powerful and flexible computer language R to underscore the significance and benefits of modern resampling techniques. The book begins by introducing permutation tests and bootstrap methods, motivating classical inference methods. Striking a balance between theory, computing, and applications, the authors explore additional topics such as: Exploratory data analysis Calculation of sampling distributions The Central Limit Theorem Monte Carlo sampling Maximum likelihood estimation and properties of estimators Confidence intervals and hypothesis tests Regression Bayesian methods Throughout the book, case studies on diverse subjects such as flight delays, birth weights of babies, and telephone company repair times illustrate the relevance of the real-world applications of the discussed material. Key definitions and theorems of important probability distributions are collected at the end of the book, and a related website is also available, featuring additional material including data sets, R scripts, and helpful teaching hints. Mathematical Statistics with Resampling and R is an excellent book for courses on mathematical statistics at the upper-undergraduate and graduate levels. It also serves as a valuable reference for applied statisticians working in the areas of business, economics, biostatistics, and public health who utilize resampling methods in their everyday work.

13486.26 RUR

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Группа авторов Aerosol Sampling


This book provides a comprehensive account of the important field of aerosol sampling as it is applied to the measurement of aerosols that are ubiquitous in occupational and living environments, both indoor and outdoor. It is written in four parts: Part A contains 9 chapters that describe the current knowledge of the physical science that underpins the process of aerosol sampling. Part B contains 4 chapters, which present the basis of standards for aerosols, including the link with human exposure by inhalation. Part C contains 7 chapters that cover the development of practical aerosol sampling instrumentation, and how technical designs and methods have evolved over the years in order that aerosol sampling may be carried out in a manner matching the health-related and other criteria that have been proposed as parts of standards. Finally Part D contains 6 chapters that describe how a wide range of aerosol sampling instruments have performed when they have been applied in the field in both occupational and ambient atmospheric environments, including how different instruments, nominally intended to measure the same aerosol fraction, compare when used side-by-side in the real world. The book draws together all that is known about aerosol sampling, for the benefit of researchers and practitioners in occupational and environmental health and all other fields of science and engineering where aerosols are of interest.

19112.98 RUR

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Группа авторов Environmental Statistics


In modern society, we are ever more aware of the environmental issues we face, whether these relate to global warming, depletion of rivers and oceans, despoliation of forests, pollution of land, poor air quality, environmental health issues, etc. At the most fundamental level it is necessary to monitor what is happening in the environment – collecting data to describe the changing scene. More importantly, it is crucial to formally describe the environment with sound and validated models, and to analyse and interpret the data we obtain in order to take action. Environmental Statistics provides a broad overview of the statistical methodology used in the study of the environment, written in an accessible style by a leading authority on the subject. It serves as both a textbook for students of environmental statistics, as well as a comprehensive source of reference for anyone working in statistical investigation of environmental issues. Provides broad coverage of the methodology used in the statistical investigation of environmental issues. Covers a wide range of key topics, including sampling, methods for extreme data, outliers and robustness, relationship models and methods, time series, spatial analysis, and environmental standards. Includes many detailed practical and worked examples that illustrate the applications of statistical methods in environmental issues. Authored by a leading authority on environmental statistics.

13932.83 RUR

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Группа авторов Statistics at Square Two


Updated companion volume to the ever popular Statistics at Square One (SS1) Statistics at Square Two, Second Edition, helps you evaluate the many statistical methods in current use. Going beyond the basics of SS1, it covers sophisticated methods and highlights misunderstandings. Easy to read, it includes annotated computer outputs and keeps formulas to a minimum. Worked examples of methods such as multiple and logical regression reinforce the text. Each chapter concludes with exercises to stimulate learning. All those who need to understand statistics in clinical research papers and apply them in their own research will value this compact and coherent guide.

4193.25 RUR

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