Download or read book Introduction to Probability and Statistics from a Bayesian Viewpoint Probability written by Dennis Victor Lindley and published by . This book was released on 1965 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Introduction to Probability and Statistics from a Bayesian View Point written by Dennis Victor Lindley and published by . This book was released on 1980 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Introduction to Probability and Statistics from a Bayesian Viewpoint Part 1 Probability written by D. V. Lindley and published by Cambridge University Press. This book was released on 1965-01-02 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two parts of this book treat probability and statistics as mathematical disciplines and with the same degree of rigour as is adopted for other branches of applied mathematics at the level of a British honours degree. They contain the minimum information about these subjects that any honours graduate in mathematics ought to know. They are written primarily for general mathematicians, rather than for statistical specialists or for natural scientists who need to use statistics in their work. No previous knowledge of probability or statistics is assumed, though familiarity with calculus and linear algebra is required. The first volume takes the theory of probability sufficiently far to be able to discuss the simpler random processes, for example, queueing theory and random walks. The second volume deals with statistics, the theory of making valid inferences from experimental data, and includes an account of the methods of least squares and maximum likelihood; it uses the results of the first volume.
Download or read book Introduction to Probability and Statistics from a Bayesian Viewpoint written by Dennis Victor Lindley and published by . This book was released on 1969 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Introduction to Probability and Statistics from a Bayesian Viewpoint Part 1 Probability written by D. V. Lindley and published by Cambridge University Press. This book was released on 1980-03-20 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two parts of this book treat probability and statistics as mathematical disciplines and with the same degree of rigour as is adopted for other branches of applied mathematics at the level of a British honours degree. They contain the minimum information about these subjects that any honours graduate in mathematics ought to know. They are written primarily for general mathematicians, rather than for statistical specialists or for natural scientists who need to use statistics in their work. No previous knowledge of probability or statistics is assumed, though familiarity with calculus and linear algebra is required. The first volume takes the theory of probability sufficiently far to be able to discuss the simpler random processes, for example, queueing theory and random walks. The second volume deals with statistics, the theory of making valid inferences from experimental data, and includes an account of the methods of least squares and maximum likelihood; it uses the results of the first volume.
Download or read book Introduction to Probability and Statistics Using R written by G. Jay Kerns and published by Lulu.com. This book was released on 2010-01-10 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a textbook for an undergraduate course in probability and statistics. The approximate prerequisites are two or three semesters of calculus and some linear algebra. Students attending the class include mathematics, engineering, and computer science majors.
Download or read book Introduction to Probability and Statistics written by Giri and published by Routledge. This book was released on 2019-01-22 with total page 570 pages. Available in PDF, EPUB and Kindle. Book excerpt: Beginning with the historical background of probability theory, this thoroughly revised text examines all important aspects of mathematical probability - including random variables, probability distributions, characteristic and generating functions, stochatic convergence, and limit theorems - and provides an introduction to various types of statistical problems, covering the broad range of statistical inference.;Requiring a prerequisite in calculus for complete understanding of the topics discussed, the Second Edition contains new material on: univariate distributions; multivariate distributions; large-sample methods; decision theory; and applications of ANOVA.;A primary text for a year-long undergraduate course in statistics (but easily adapted for a one-semester course in probability only), Introduction to Probability and Statistics is for undergraduate students in a wide range of disciplines-statistics, probability, mathematics, social science, economics, engineering, agriculture, biometry, and education.
Download or read book Probability and Bayesian Modeling written by Jim Albert and published by CRC Press. This book was released on 2019-12-06 with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probability and Bayesian Modeling is an introduction to probability and Bayesian thinking for undergraduate students with a calculus background. The first part of the book provides a broad view of probability including foundations, conditional probability, discrete and continuous distributions, and joint distributions. Statistical inference is presented completely from a Bayesian perspective. The text introduces inference and prediction for a single proportion and a single mean from Normal sampling. After fundamentals of Markov Chain Monte Carlo algorithms are introduced, Bayesian inference is described for hierarchical and regression models including logistic regression. The book presents several case studies motivated by some historical Bayesian studies and the authors’ research. This text reflects modern Bayesian statistical practice. Simulation is introduced in all the probability chapters and extensively used in the Bayesian material to simulate from the posterior and predictive distributions. One chapter describes the basic tenets of Metropolis and Gibbs sampling algorithms; however several chapters introduce the fundamentals of Bayesian inference for conjugate priors to deepen understanding. Strategies for constructing prior distributions are described in situations when one has substantial prior information and for cases where one has weak prior knowledge. One chapter introduces hierarchical Bayesian modeling as a practical way of combining data from different groups. There is an extensive discussion of Bayesian regression models including the construction of informative priors, inference about functions of the parameters of interest, prediction, and model selection. The text uses JAGS (Just Another Gibbs Sampler) as a general-purpose computational method for simulating from posterior distributions for a variety of Bayesian models. An R package ProbBayes is available containing all of the book datasets and special functions for illustrating concepts from the book. A complete solutions manual is available for instructors who adopt the book in the Additional Resources section.
Download or read book Basic Concepts of Probability and Statistics written by J. L. Hodges, Jr. and published by SIAM. This book was released on 2004-12-01 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a mathematically rigorous introduction to the fundamental ideas of modern statistics for readers without a calculus background.
Download or read book Statistical Methods in Medical Research written by Peter Armitage and published by John Wiley & Sons. This book was released on 2013-07-01 with total page 664 pages. Available in PDF, EPUB and Kindle. Book excerpt: The explanation and implementation of statistical methods for the medical researcher or statistician remains an integral part of modern medical research. This book explains the use of experimental and analytical biostatistics systems. Its accessible style allows it to be used by the non-mathematician as a fundamental component of successful research. Since the third edition, there have been many developments in statistical techniques. The fourth edition provides the medical statistician with an accessible guide to these techniques and to reflect the extent of their usage in medical research. The new edition takes a much more comprehensive approach to its subject. There has been a radical reorganization of the text to improve the continuity and cohesion of the presentation and to extend the scope by covering many new ideas now being introduced into the analysis of medical research data. The authors have tried to maintain the modest level of mathematical exposition that characterized the earlier editions, essentially confining the mathematics to the statement of algebraic formulae rather than pursuing mathematical proofs. Received the Highly Commended Certificate in the Public Health Category of the 2002 BMA Books Competition.
Download or read book Bayesian Methods written by Jeff Gill and published by CRC Press. This book was released on 2007-11-26 with total page 696 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first edition of Bayesian Methods: A Social and Behavioral Sciences Approach helped pave the way for Bayesian approaches to become more prominent in social science methodology. While the focus remains on practical modeling and basic theory as well as on intuitive explanations and derivations without skipping steps, this second edition incorpora
Download or read book The Collected Works of John W Tukey written by L.V. Jones and published by CRC Press. This book was released on 1987-05-15 with total page 630 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume of eleven articles compiles important papers by Tukey that examine the intriguing problems inherent in the area of multiple comparisons and provide a useful framework for thinking about them. Each volume in the set is indexed and contains a bibliography.
Download or read book An Introduction to Probability and Statistics written by Beryl Hume and published by . This book was released on 1966 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book The Logic of Strategy written by Cristina Bicchieri and published by Oxford University Press, USA. This book was released on 1999 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: Edited by three leading figures in the field, this exciting volume presents cutting-edge work in decision theory by a distinguished international roster of contributors. These mostly unpublished papers address a host of crucial areas in the contemporary philosophical study of rationality and knowledge. Topics include causal versus evidential decision theory, game theory, backwards induction, bounded rationality, counterfactual reasoning in games and in general, analyses of the famous common knowledge assumptions in game theory, and evaluations of the normal versus extensive form formulations of complex decision problems.
Download or read book Comparative Statistical Inference written by Vic Barnett and published by John Wiley & Sons. This book was released on 2009-09-25 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Handbook of Utility Theory written by Salvador Barbera and published by Springer Science & Business Media. This book was released on 2004-03-31 with total page 636 pages. Available in PDF, EPUB and Kindle. Book excerpt: The standard rationality hypothesis is that behaviour can be represented as the maximization of a suitably restricted utility function. This hypothesis lies at the heart of a large body of recent work in economics, of course, but also in political science, ethics, and other major branches of the social sciences. Though this hypothesis of utility maximization deserves our continued respect, finding further refinements and developing new critiques remain areas of active research. In fact, many fundamental conceptual problems remain unsettled. Where others have been resolved, their resolutions may be too recent to have achieved widespread understanding among social scientists. Last but not least, a growing number of papers attempt to challenge the rationality hypothesis head on, at least in its more orthodox formulation. The main purpose of this Handbook is to make more widely available some recent developments in the area. Yet we are well aware that the final chapter of a handbook like this can never be written as long as the area of research remains active, as is certainly the case with utility theory. The editors originally selected a list of topics that seemed ripe enough at the time that the book was planned. Then they invited contributions from researchers whose work had come to their attention. So the list of topics and contributors is largely the editors' responsibility, although some potential con tributors did decline our invitation. Each chapter has also been refereed, and often significantly revised in the light of the referees' remarks.
Download or read book A Course in Statistics with R written by Prabhanjan N. Tattar and published by John Wiley & Sons. This book was released on 2016-03-15 with total page 696 pages. Available in PDF, EPUB and Kindle. Book excerpt: Integrates the theory and applications of statistics using R A Course in Statistics with R has been written to bridge the gap between theory and applications and explain how mathematical expressions are converted into R programs. The book has been primarily designed as a useful companion for a Masters student during each semester of the course, but will also help applied statisticians in revisiting the underpinnings of the subject. With this dual goal in mind, the book begins with R basics and quickly covers visualization and exploratory analysis. Probability and statistical inference, inclusive of classical, nonparametric, and Bayesian schools, is developed with definitions, motivations, mathematical expression and R programs in a way which will help the reader to understand the mathematical development as well as R implementation. Linear regression models, experimental designs, multivariate analysis, and categorical data analysis are treated in a way which makes effective use of visualization techniques and the related statistical techniques underlying them through practical applications, and hence helps the reader to achieve a clear understanding of the associated statistical models. Key features: Integrates R basics with statistical concepts Provides graphical presentations inclusive of mathematical expressions Aids understanding of limit theorems of probability with and without the simulation approach Presents detailed algorithmic development of statistical models from scratch Includes practical applications with over 50 data sets
