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Applied Statistical Inference
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Book Synopsis Likelihood and Bayesian Inference by : Leonhard Held
Download or read book Likelihood and Bayesian Inference written by Leonhard Held and published by Springer Nature. This book was released on 2020-03-31 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: This richly illustrated textbook covers modern statistical methods with applications in medicine, epidemiology and biology. Firstly, it discusses the importance of statistical models in applied quantitative research and the central role of the likelihood function, describing likelihood-based inference from a frequentist viewpoint, and exploring the properties of the maximum likelihood estimate, the score function, the likelihood ratio and the Wald statistic. In the second part of the book, likelihood is combined with prior information to perform Bayesian inference. Topics include Bayesian updating, conjugate and reference priors, Bayesian point and interval estimates, Bayesian asymptotics and empirical Bayes methods. It includes a separate chapter on modern numerical techniques for Bayesian inference, and also addresses advanced topics, such as model choice and prediction from frequentist and Bayesian perspectives. This revised edition of the book “Applied Statistical Inference” has been expanded to include new material on Markov models for time series analysis. It also features a comprehensive appendix covering the prerequisites in probability theory, matrix algebra, mathematical calculus, and numerical analysis, and each chapter is complemented by exercises. The text is primarily intended for graduate statistics and biostatistics students with an interest in applications.
Book Synopsis Applied Statistical Inference by : Leonhard Held
Download or read book Applied Statistical Inference written by Leonhard Held and published by Springer Science & Business Media. This book was released on 2013-11-12 with total page 381 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers modern statistical inference based on likelihood with applications in medicine, epidemiology and biology. Two introductory chapters discuss the importance of statistical models in applied quantitative research and the central role of the likelihood function. The rest of the book is divided into three parts. The first describes likelihood-based inference from a frequentist viewpoint. Properties of the maximum likelihood estimate, the score function, the likelihood ratio and the Wald statistic are discussed in detail. In the second part, likelihood is combined with prior information to perform Bayesian inference. Topics include Bayesian updating, conjugate and reference priors, Bayesian point and interval estimates, Bayesian asymptotics and empirical Bayes methods. Modern numerical techniques for Bayesian inference are described in a separate chapter. Finally two more advanced topics, model choice and prediction, are discussed both from a frequentist and a Bayesian perspective. A comprehensive appendix covers the necessary prerequisites in probability theory, matrix algebra, mathematical calculus, and numerical analysis.
Book Synopsis Statistical Inference by : S.D. Silvey
Download or read book Statistical Inference written by S.D. Silvey and published by Routledge. This book was released on 2017-10-19 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistics is a subject with a vast field of application, involving problems which vary widely in their character and complexity.However, in tackling these, we use a relatively small core of central ideas and methods. This book attempts to concentrateattention on these ideas: they are placed in a general settingand illustrated by relatively simple examples, avoidingwherever possible the extraneous difficulties of complicatedmathematical manipulation.In order to compress the central body of ideas into a smallvolume, it is necessary to assume a fair degree of mathematicalsophistication on the part of the reader, and the book is intendedfor students of mathematics who are already accustomed tothinking in rather general terms about spaces and functions
Book Synopsis Statistical Inference Based on the likelihood by : Adelchi Azzalini
Download or read book Statistical Inference Based on the likelihood written by Adelchi Azzalini and published by Routledge. This book was released on 2017-11-13 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Likelihood plays a key role in both introducing general notions of statistical theory, and in developing specific methods. This book introduces likelihood-based statistical theory and related methods from a classical viewpoint, and demonstrates how the main body of currently used statistical techniques can be generated from a few key concepts, in particular the likelihood. Focusing on those methods, which have both a solid theoretical background and practical relevance, the author gives formal justification of the methods used and provides numerical examples with real data.
Book Synopsis Applied Statistical Inference with MINITAB®, Second Edition by : Sally A. Lesik
Download or read book Applied Statistical Inference with MINITAB®, Second Edition written by Sally A. Lesik and published by CRC Press. This book was released on 2018-12-07 with total page 475 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the first edition: "One of my biggest complaints when I teach introductory statistics classes is that it takes me most of the semester to get to the good stuff—inferential statistics. The author manages to do this very quickly....if one were looking for a book that efficiently covers basic statistical methodology and also introduces statistical software [this text] fits the bill." -The American Statistician Applied Statistical Inference with MINITAB, Second Edition distinguishes itself from other introductory statistics textbooks by focusing on the applications of statistics without compromising mathematical rigor. It presents the material in a seamless step-by-step approach so that readers are first introduced to a topic, given the details of the underlying mathematical foundations along with a detailed description of how to interpret the findings, and are shown how to use the statistical software program Minitab to perform the same analysis. Gives readers a solid foundation in how to apply many different statistical methods. MINITAB is fully integrated throughout the text. Includes fully worked out examples so students can easily follow the calculations. Presents many new topics such as one- and two-sample variances, one- and two-sample Poisson rates, and more nonparametric statistics. Features mostly new exercises as well as the addition of Best Practices sections that describe some common pitfalls and provide some practical advice on statistical inference. This book is written to be user-friendly for students and practitioners who are not experts in statistics, but who want to gain a solid understanding of basic statistical inference. This book is oriented towards the practical use of statistics. The examples, discussions, and exercises are based on data and scenarios that are common to students in their everyday lives.
Book Synopsis Statistical Inference Via Convex Optimization by : Anatoli Juditsky
Download or read book Statistical Inference Via Convex Optimization written by Anatoli Juditsky and published by Princeton University Press. This book was released on 2020-04-07 with total page 655 pages. Available in PDF, EPUB and Kindle. Book excerpt: This authoritative book draws on the latest research to explore the interplay of high-dimensional statistics with optimization. Through an accessible analysis of fundamental problems of hypothesis testing and signal recovery, Anatoli Juditsky and Arkadi Nemirovski show how convex optimization theory can be used to devise and analyze near-optimal statistical inferences. Statistical Inference via Convex Optimization is an essential resource for optimization specialists who are new to statistics and its applications, and for data scientists who want to improve their optimization methods. Juditsky and Nemirovski provide the first systematic treatment of the statistical techniques that have arisen from advances in the theory of optimization. They focus on four well-known statistical problems—sparse recovery, hypothesis testing, and recovery from indirect observations of both signals and functions of signals—demonstrating how they can be solved more efficiently as convex optimization problems. The emphasis throughout is on achieving the best possible statistical performance. The construction of inference routines and the quantification of their statistical performance are given by efficient computation rather than by analytical derivation typical of more conventional statistical approaches. In addition to being computation-friendly, the methods described in this book enable practitioners to handle numerous situations too difficult for closed analytical form analysis, such as composite hypothesis testing and signal recovery in inverse problems. Statistical Inference via Convex Optimization features exercises with solutions along with extensive appendixes, making it ideal for use as a graduate text.
Book Synopsis Statistical Inference by : George Casella
Download or read book Statistical Inference written by George Casella and published by CRC Press. This book was released on 2024-05-23 with total page 1746 pages. Available in PDF, EPUB and Kindle. Book excerpt: This classic textbook builds theoretical statistics from the first principles of probability theory. Starting from the basics of probability, the authors develop the theory of statistical inference using techniques, definitions, and concepts that are statistical and natural extensions, and consequences, of previous concepts. It covers all topics from a standard inference course including: distributions, random variables, data reduction, point estimation, hypothesis testing, and interval estimation. Features The classic graduate-level textbook on statistical inference Develops elements of statistical theory from first principles of probability Written in a lucid style accessible to anyone with some background in calculus Covers all key topics of a standard course in inference Hundreds of examples throughout to aid understanding Each chapter includes an extensive set of graduated exercises Statistical Inference, Second Edition is primarily aimed at graduate students of statistics, but can be used by advanced undergraduate students majoring in statistics who have a solid mathematics background. It also stresses the more practical uses of statistical theory, being more concerned with understanding basic statistical concepts and deriving reasonable statistical procedures, while less focused on formal optimality considerations. This is a reprint of the second edition originally published by Cengage Learning, Inc. in 2001.
Book Synopsis Topics on Methodological and Applied Statistical Inference by : Tonio Di Battista
Download or read book Topics on Methodological and Applied Statistical Inference written by Tonio Di Battista and published by Springer. This book was released on 2016-10-11 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together selected peer-reviewed contributions from various research fields in statistics, and highlights the diverse approaches and analyses related to real-life phenomena. Major topics covered in this volume include, but are not limited to, bayesian inference, likelihood approach, pseudo-likelihoods, regression, time series, and data analysis as well as applications in the life and social sciences. The software packages used in the papers are made available by the authors. This book is a result of the 47th Scientific Meeting of the Italian Statistical Society, held at the University of Cagliari, Italy, in 2014.
Book Synopsis Some Basic Theory for Statistical Inference by : E.J.G. Pitman
Download or read book Some Basic Theory for Statistical Inference written by E.J.G. Pitman and published by CRC Press. This book was released on 2018-01-18 with total page 61 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book the author presents with elegance and precision some of the basic mathematical theory required for statistical inference at a level which will make it readable by most students of statistics.
Book Synopsis Statistical Inference by : Helio S. Migon
Download or read book Statistical Inference written by Helio S. Migon and published by CRC Press. This book was released on 2014-09-03 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Balanced Treatment of Bayesian and Frequentist Inference Statistical Inference: An Integrated Approach, Second Edition presents an account of the Bayesian and frequentist approaches to statistical inference. Now with an additional author, this second edition places a more balanced emphasis on both perspectives than the first edition. New to the Second Edition New material on empirical Bayes and penalized likelihoods and their impact on regression models Expanded material on hypothesis testing, method of moments, bias correction, and hierarchical models More examples and exercises More comparison between the approaches, including their similarities and differences Designed for advanced undergraduate and graduate courses, the text thoroughly covers statistical inference without delving too deep into technical details. It compares the Bayesian and frequentist schools of thought and explores procedures that lie on the border between the two. Many examples illustrate the methods and models, and exercises are included at the end of each chapter.
Book Synopsis Principles of Statistical Inference by : D. R. Cox
Download or read book Principles of Statistical Inference written by D. R. Cox and published by Cambridge University Press. This book was released on 2006-08-10 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Applied Statistical Inference with MINITAB®, Second Edition by : Sally A. Lesik
Download or read book Applied Statistical Inference with MINITAB®, Second Edition written by Sally A. Lesik and published by CRC Press. This book was released on 2018-12-07 with total page 478 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the first edition: "One of my biggest complaints when I teach introductory statistics classes is that it takes me most of the semester to get to the good stuff—inferential statistics. The author manages to do this very quickly....if one were looking for a book that efficiently covers basic statistical methodology and also introduces statistical software [this text] fits the bill." -The American Statistician Applied Statistical Inference with MINITAB, Second Edition distinguishes itself from other introductory statistics textbooks by focusing on the applications of statistics without compromising mathematical rigor. It presents the material in a seamless step-by-step approach so that readers are first introduced to a topic, given the details of the underlying mathematical foundations along with a detailed description of how to interpret the findings, and are shown how to use the statistical software program Minitab to perform the same analysis. Gives readers a solid foundation in how to apply many different statistical methods. MINITAB is fully integrated throughout the text. Includes fully worked out examples so students can easily follow the calculations. Presents many new topics such as one- and two-sample variances, one- and two-sample Poisson rates, and more nonparametric statistics. Features mostly new exercises as well as the addition of Best Practices sections that describe some common pitfalls and provide some practical advice on statistical inference. This book is written to be user-friendly for students and practitioners who are not experts in statistics, but who want to gain a solid understanding of basic statistical inference. This book is oriented towards the practical use of statistics. The examples, discussions, and exercises are based on data and scenarios that are common to students in their everyday lives.
Book Synopsis Applied Bayesian and Classical Inference by : F. Mosteller
Download or read book Applied Bayesian and Classical Inference written by F. Mosteller and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: The new version has two additions. First, at the suggestion of Stephen Stigler I we have replaced the Table of Contents by what he calls an Analytic Table of Contents. Following the title of each section or subsection is a description of the content of the section. This material helps the reader in several ways, for example: by giving a synopsis of the book, by explaining where the various data tables are and what they deal with, by telling what theory is described where. We did several distinct full studies for the Federalist papers as well as many minor side studies. Some or all may offer information both to the applied and the theoretical reader. We therefore try to give in this Contents more than the few cryptic words in a section heading to ~peed readers in finding what they want. Seconq, we have prepared an extra chapter dealing with authorship work published from. about 1969 to 1983. Although a chapter cannot compre hensively Gover a field where many books now appear, it can mention most ofthe book-length works and the main thread of authorship' studies published in English. We founq biblical authorship studies so extensive and com plicated that we thought it worthwhile to indicate some papers that would bring out the controversies that are taking place. We hope we have given the flavor of developments over the 15 years mentioned. We have also corrected a few typographical errors.
Book Synopsis Semimartingales and their Statistical Inference by : B.L.S. Prakasa Rao
Download or read book Semimartingales and their Statistical Inference written by B.L.S. Prakasa Rao and published by CRC Press. This book was released on 1999-05-11 with total page 684 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical inference carries great significance in model building from both the theoretical and the applications points of view. Its applications to engineering and economic systems, financial economics, and the biological and medical sciences have made statistical inference for stochastic processes a well-recognized and important branch of statistics and probability. The class of semimartingales includes a large class of stochastic processes, including diffusion type processes, point processes, and diffusion type processes with jumps, widely used for stochastic modeling. Until now, however, researchers have had no single reference that collected the research conducted on the asymptotic theory for semimartingales. Semimartingales and their Statistical Inference, fills this need by presenting a comprehensive discussion of the asymptotic theory of semimartingales at a level needed for researchers working in the area of statistical inference for stochastic processes. The author brings together into one volume the state-of-the-art in the inferential aspect for such processes. The topics discussed include: Asymptotic likelihood theory Quasi-likelihood Likelihood and efficiency Inference for counting processes Inference for semimartingale regression models The author addresses a number of stochastic modeling applications from engineering, economic systems, financial economics, and medical sciences. He also includes some of the new and challenging statistical and probabilistic problems facing today's active researchers working in the area of inference for stochastic processes.
Book Synopsis Applied Statistical Inference with MINITAB by : Sally A. Lesik
Download or read book Applied Statistical Inference with MINITAB written by Sally A. Lesik and published by CRC Press. This book was released on 2009-12-21 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: Through clear, step-by-step mathematical calculations, Applied Statistical Inference with MINITAB enables students to gain a solid understanding of how to apply statistical techniques using a statistical software program. It focuses on the concepts of confidence intervals, hypothesis testing, validating model assumptions, and power analysis.Illustr
Book Synopsis Handbook Of Applied Econometrics And Statistical Inference by : Aman Ullah
Download or read book Handbook Of Applied Econometrics And Statistical Inference written by Aman Ullah and published by CRC Press. This book was released on 2002-01-29 with total page 741 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summarizes developments and techniques in the field. It highlights areas such as sample surveys, nonparametic analysis, hypothesis testing, time series analysis, Bayesian inference, and distribution theory for applications in statistics, economics, medicine, biology, and engineering.
Book Synopsis Modern Applied Statistics with S-PLUS by : William N. Venables
Download or read book Modern Applied Statistics with S-PLUS written by William N. Venables and published by Springer Science & Business Media. This book was released on 2013-11-11 with total page 562 pages. Available in PDF, EPUB and Kindle. Book excerpt: A guide to using the power of S-PLUS to perform statistical analyses, providing both an introduction to the program and a course in modern statistical methods. Readers are assumed to have a basic grounding in statistics, thus the book is intended for would-be users, as well as students and researchers using statistics. Throughout, the emphasis is on presenting practical problems and full analyses of real data sets, with many of the methods discussed being modern approaches to topics such as linear and non-linear regression models, robust and smooth regression methods, survival analysis, multivariate analysis, tree-based methods, time series, spatial statistics, and classification. This second edition is intended for users of S-PLUS 3.3, or later, and covers both Windows and UNIX. It treats the recent developments in graphics and new statistical functionality, including bootstraping, mixed effects linear and non-linear models, factor analysis, and regression with autocorrelated errors. The authors have written several software libraries which enhance S-PLUS, and these, plus all the datasets used, are available on the Internet.
