The Bayesian Way Introductory Statistics For Economists And Engineers

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The Bayesian Way: Introductory Statistics for Economists and Engineers

Author : Svein Olav Nyberg
Publisher : John Wiley & Sons
ISBN 13 : 1119246873
Total Pages : 512 pages
Book Rating : 4.1/5 (192 download)

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Book Synopsis The Bayesian Way: Introductory Statistics for Economists and Engineers by : Svein Olav Nyberg

Download or read book The Bayesian Way: Introductory Statistics for Economists and Engineers written by Svein Olav Nyberg and published by John Wiley & Sons. This book was released on 2018-08-28 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive resource that offers an introduction to statistics with a Bayesian angle, for students of professional disciplines like engineering and economics The Bayesian Way offers a basic introduction to statistics that emphasizes the Bayesian approach and is designed for use by those studying professional disciplines like engineering and economics. In addition to the Bayesian approach, the author includes the most common techniques of the frequentist approach. Throughout the text, the author covers statistics from a basic to a professional working level along with a practical understanding of the matter at hand. Filled with helpful illustrations, this comprehensive text explores a wide range of topics, starting with descriptive statistics, set theory, and combinatorics. The text then goes on to review fundamental probability theory and Bayes' theorem. The first part ends in an exposition of stochastic variables, exploring discrete, continuous and mixed probability distributions. In the second part, the book looks at statistical inference. Primarily Bayesian, but with the main frequentist techniques included, it covers conjugate priors through the powerful yet simple method of hyperparameters. It then goes on to topics in hypothesis testing (including utility functions), point and interval estimates (including frequentist confidence intervals), and linear regression. This book: Explains basic statistics concepts in accessible terms and uses an abundance of illustrations to enhance visual understanding Has guides for how to calculate the different probability distributions, functions , and statistical properties, on platforms like popular pocket calculators and Mathematica / Wolfram Alpha Includes example-proofs that enable the reader to follow the reasoning Contains assignments at different levels of difficulty from simply filling out the correct formula to the complex multi-step text assignments Offers information on continuous, discrete and mixed probability distributions, hypothesis testing, credible and confidence intervals, and linear regression Written for undergraduate and graduate students of subjects where Bayesian statistics are applied, including engineering, economics, and related fields, The Bayesian Way: With Applications in Engineering and Economics offers a clear understanding of Bayesian statistics that have real-world applications.

Statistics

Author : David W. Scott
Publisher : John Wiley & Sons
ISBN 13 : 1119675847
Total Pages : 180 pages
Book Rating : 4.1/5 (196 download)

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Book Synopsis Statistics by : David W. Scott

Download or read book Statistics written by David W. Scott and published by John Wiley & Sons. This book was released on 2020-07-13 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistic: A Concise Mathematical Introduction for Students and Scientists offers a one academic term text that prepares the student to broaden their skills in statistics, probability and inference, prior to selecting their follow-on courses in their chosen fields, whether it be engineering, computer science, programming, data sciences, business or economics. The book places focus early on continuous measurements, as well as discrete random variables. By invoking simple and intuitive models and geometric probability, discrete and continuous experiments and probabilities are discussed throughout the book in a natural way. Classical probability, random variables, and inference are discussed, as well as material on understanding data and topics of special interest. Topics discussed include: • Classical equally likely outcomes • Variety of models of discrete and continuous probability laws • Likelihood function and ratio • Inference • Bayesian statistics With the growth in the volume of data generated in many disciplines that is enabling the growth in data science, companies now demand statistically literate scientists and this textbook is the answer, suited for undergraduates studying science or engineering, be it computer science, economics, life sciences, environmental, business, amongst many others. Basic knowledge of bivariate calculus, R language, Matematica and JMP is useful, however there is an accompanying website including sample R and Mathematica code to help instructors and students.

Bayesian Data Analysis, Third Edition

Author : Andrew Gelman
Publisher : CRC Press
ISBN 13 : 1439840954
Total Pages : 677 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Bayesian Data Analysis, Third Edition by : Andrew Gelman

Download or read book Bayesian Data Analysis, Third Edition written by Andrew Gelman and published by CRC Press. This book was released on 2013-11-01 with total page 677 pages. Available in PDF, EPUB and Kindle. Book excerpt: Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors—all leaders in the statistics community—introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice. New to the Third Edition Four new chapters on nonparametric modeling Coverage of weakly informative priors and boundary-avoiding priors Updated discussion of cross-validation and predictive information criteria Improved convergence monitoring and effective sample size calculations for iterative simulation Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation New and revised software code The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book’s web page.

Data Analysis

Author : Devinderjit Sivia
Publisher : OUP Oxford
ISBN 13 : 0191546704
Total Pages : 264 pages
Book Rating : 4.1/5 (915 download)

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Book Synopsis Data Analysis by : Devinderjit Sivia

Download or read book Data Analysis written by Devinderjit Sivia and published by OUP Oxford. This book was released on 2006-06-02 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the strengths of this book is the author's ability to motivate the use of Bayesian methods through simple yet effective examples. - Katie St. Clair MAA Reviews.

An Introduction to Bayesian Inference in Econometrics

Author : Arnold Zellner
Publisher : New York : J. Wiley
ISBN 13 :
Total Pages : 456 pages
Book Rating : 4.:/5 (321 download)

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Book Synopsis An Introduction to Bayesian Inference in Econometrics by : Arnold Zellner

Download or read book An Introduction to Bayesian Inference in Econometrics written by Arnold Zellner and published by New York : J. Wiley. This book was released on 1971-11-26 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: Remarks on inference in economics; Principles of bayesian analysis with selected applications; The univariate normal linear regression model; Special problems in regression analysis; On error in the variables; Analysis of single equation nonlinear models; Time series models: some selected examples; Multivariate regression models; Simultaneous equation econometric models; On comparing and testing hypotheses; Analysis of some control problems.

Introduction to Probability and Statistics for Engineers and Scientists

Author : Sheldon M. Ross
Publisher :
ISBN 13 :
Total Pages : 532 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Introduction to Probability and Statistics for Engineers and Scientists by : Sheldon M. Ross

Download or read book Introduction to Probability and Statistics for Engineers and Scientists written by Sheldon M. Ross and published by . This book was released on 1987 with total page 532 pages. Available in PDF, EPUB and Kindle. Book excerpt: Elements of probability; Random variables and expectation; Special; random variables; Sampling; Parameter estimation; Hypothesis testing; Regression; Analysis of variance; Goodness of fit and nonparametric testing; Life testing; Quality control; Simulation.

Probability and Statistics for Economists

Author : Bruce Hansen
Publisher : Princeton University Press
ISBN 13 : 0691236143
Total Pages : 417 pages
Book Rating : 4.6/5 (912 download)

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Book Synopsis Probability and Statistics for Economists by : Bruce Hansen

Download or read book Probability and Statistics for Economists written by Bruce Hansen and published by Princeton University Press. This book was released on 2022-06-28 with total page 417 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive and up-to-date introduction to the mathematics that all economics students need to know Probability theory is the quantitative language used to handle uncertainty and is the foundation of modern statistics. Probability and Statistics for Economists provides graduate and PhD students with an essential introduction to mathematical probability and statistical theory, which are the basis of the methods used in econometrics. This incisive textbook teaches fundamental concepts, emphasizes modern, real-world applications, and gives students an intuitive understanding of the mathematics that every economist needs to know. Covers probability and statistics with mathematical rigor while emphasizing intuitive explanations that are accessible to economics students of all backgrounds Discusses random variables, parametric and multivariate distributions, sampling, the law of large numbers, central limit theory, maximum likelihood estimation, numerical optimization, hypothesis testing, and more Features hundreds of exercises that enable students to learn by doing Includes an in-depth appendix summarizing important mathematical results as well as a wealth of real-world examples Can serve as a core textbook for a first-semester PhD course in econometrics and as a companion book to Bruce E. Hansen’s Econometrics Also an invaluable reference for researchers and practitioners

Bayesian Statistics

Author : Peter M. Lee
Publisher : Wiley
ISBN 13 : 9780340814055
Total Pages : 352 pages
Book Rating : 4.8/5 (14 download)

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Book Synopsis Bayesian Statistics by : Peter M. Lee

Download or read book Bayesian Statistics written by Peter M. Lee and published by Wiley. This book was released on 2009-01-20 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian Statistics is the school of thought that uses all information surrounding the likelihood of an event rather than just that collected experimentally. Among statisticians the Bayesian approach continues to gain adherents and this new edition of Peter Lee’s well-established introduction maintains the clarity of exposition and use of examples for which this text is known and praised. In addition, there is extended coverage of the Metropolis-Hastings algorithm as well as an introduction to the use of BUGS (Bayesian Inference Using Gibbs Sampling) as this is now the standard computational tool for such numerical work. Other alterations include new material on generalized linear modelling and Bernardo’s theory of reference points.

Bayesian Spectrum Analysis and Parameter Estimation

Author : G. Larry Bretthorst
Publisher : Springer Science & Business Media
ISBN 13 : 146849399X
Total Pages : 210 pages
Book Rating : 4.4/5 (684 download)

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Book Synopsis Bayesian Spectrum Analysis and Parameter Estimation by : G. Larry Bretthorst

Download or read book Bayesian Spectrum Analysis and Parameter Estimation written by G. Larry Bretthorst and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work is essentially an extensive revision of my Ph.D. dissertation, [1J. It 1S primarily a research document on the application of probability theory to the parameter estimation problem. The people who will be interested in this material are physicists, economists, and engineers who have to deal with data on a daily basis; consequently, we have included a great deal of introductory and tutorial material. Any person with the equivalent of the mathematics background required for the graduate level study of physics should be able to follow the material contained in this book, though not without eIfort. From the time the dissertation was written until now (approximately one year) our understanding of the parameter estimation problem has changed extensively. We have tried to incorporate what we have learned into this book. I am indebted to a number of people who have aided me in preparing this docu ment: Dr. C. Ray Smith, Steve Finney, Juana Sunchez, Matthew Self, and Dr. Pat Gibbons who acted as readers and editors. In addition, I must extend my deepest thanks to Dr. Joseph Ackerman for his support during the time this manuscript was being prepared.

Bayesian Core: A Practical Approach to Computational Bayesian Statistics

Author : Jean-Michel Marin
Publisher : Springer Science & Business Media
ISBN 13 : 0387389830
Total Pages : 265 pages
Book Rating : 4.3/5 (873 download)

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Book Synopsis Bayesian Core: A Practical Approach to Computational Bayesian Statistics by : Jean-Michel Marin

Download or read book Bayesian Core: A Practical Approach to Computational Bayesian Statistics written by Jean-Michel Marin and published by Springer Science & Business Media. This book was released on 2007-05-26 with total page 265 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Bayesian modeling book is intended for practitioners and applied statisticians looking for a self-contained entry to computational Bayesian statistics. Focusing on standard statistical models and backed up by discussed real datasets available from the book website, it provides an operational methodology for conducting Bayesian inference, rather than focusing on its theoretical justifications. Special attention is paid to the derivation of prior distributions in each case and specific reference solutions are given for each of the models. Similarly, computational details are worked out to lead the reader towards an effective programming of the methods given in the book.

Introductory Statistics

Author : Douglas S. Shafer
Publisher :
ISBN 13 : 9781453388945
Total Pages : 0 pages
Book Rating : 4.3/5 (889 download)

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Book Synopsis Introductory Statistics by : Douglas S. Shafer

Download or read book Introductory Statistics written by Douglas S. Shafer and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Introduction to Modern Bayesian Econometrics

Author : Tony Lancaster
Publisher : Wiley-Blackwell
ISBN 13 : 9781405117203
Total Pages : 416 pages
Book Rating : 4.1/5 (172 download)

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Book Synopsis Introduction to Modern Bayesian Econometrics by : Tony Lancaster

Download or read book Introduction to Modern Bayesian Econometrics written by Tony Lancaster and published by Wiley-Blackwell. This book was released on 2004-06-18 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this new and expanding area, Tony Lancaster’s text is the first comprehensive introduction to the Bayesian way of doing applied economics. Uses clear explanations and practical illustrations and problems to present innovative, computer-intensive ways for applied economists to use the Bayesian method; Emphasizes computation and the study of probability distributions by computer sampling; Covers all the standard econometric models, including linear and non-linear regression using cross-sectional, time series, and panel data; Details causal inference and inference about structural econometric models; Includes numerical and graphical examples in each chapter, demonstrating their solutions using the S programming language and Bugs software Supported by online supplements, including Data Sets and Solutions to Problems, at www.blackwellpublishing.com/lancaster

An Introduction to Probability and Statistics

Author : Vijay K. Rohatgi
Publisher : John Wiley & Sons
ISBN 13 : 1118799658
Total Pages : 728 pages
Book Rating : 4.1/5 (187 download)

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Book Synopsis An Introduction to Probability and Statistics by : Vijay K. Rohatgi

Download or read book An Introduction to Probability and Statistics written by Vijay K. Rohatgi and published by John Wiley & Sons. This book was released on 2015-09-01 with total page 728 pages. Available in PDF, EPUB and Kindle. Book excerpt: A well-balanced introduction to probability theory and mathematical statistics Featuring updated material, An Introduction to Probability and Statistics, Third Edition remains a solid overview to probability theory and mathematical statistics. Divided intothree parts, the Third Edition begins by presenting the fundamentals and foundationsof probability. The second part addresses statistical inference, and the remainingchapters focus on special topics. An Introduction to Probability and Statistics, Third Edition includes: A new section on regression analysis to include multiple regression, logistic regression, and Poisson regression A reorganized chapter on large sample theory to emphasize the growing role of asymptotic statistics Additional topical coverage on bootstrapping, estimation procedures, and resampling Discussions on invariance, ancillary statistics, conjugate prior distributions, and invariant confidence intervals Over 550 problems and answers to most problems, as well as 350 worked out examples and 200 remarks Numerous figures to further illustrate examples and proofs throughout An Introduction to Probability and Statistics, Third Edition is an ideal reference and resource for scientists and engineers in the fields of statistics, mathematics, physics, industrial management, and engineering. The book is also an excellent text for upper-undergraduate and graduate-level students majoring in probability and statistics.

Understanding Computational Bayesian Statistics

Author : William M. Bolstad
Publisher : John Wiley & Sons
ISBN 13 : 1118209923
Total Pages : 255 pages
Book Rating : 4.1/5 (182 download)

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Book Synopsis Understanding Computational Bayesian Statistics by : William M. Bolstad

Download or read book Understanding Computational Bayesian Statistics written by William M. Bolstad and published by John Wiley & Sons. This book was released on 2011-09-20 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: A hands-on introduction to computational statistics from a Bayesian point of view Providing a solid grounding in statistics while uniquely covering the topics from a Bayesian perspective, Understanding Computational Bayesian Statistics successfully guides readers through this new, cutting-edge approach. With its hands-on treatment of the topic, the book shows how samples can be drawn from the posterior distribution when the formula giving its shape is all that is known, and how Bayesian inferences can be based on these samples from the posterior. These ideas are illustrated on common statistical models, including the multiple linear regression model, the hierarchical mean model, the logistic regression model, and the proportional hazards model. The book begins with an outline of the similarities and differences between Bayesian and the likelihood approaches to statistics. Subsequent chapters present key techniques for using computer software to draw Monte Carlo samples from the incompletely known posterior distribution and performing the Bayesian inference calculated from these samples. Topics of coverage include: Direct ways to draw a random sample from the posterior by reshaping a random sample drawn from an easily sampled starting distribution The distributions from the one-dimensional exponential family Markov chains and their long-run behavior The Metropolis-Hastings algorithm Gibbs sampling algorithm and methods for speeding up convergence Markov chain Monte Carlo sampling Using numerous graphs and diagrams, the author emphasizes a step-by-step approach to computational Bayesian statistics. At each step, important aspects of application are detailed, such as how to choose a prior for logistic regression model, the Poisson regression model, and the proportional hazards model. A related Web site houses R functions and Minitab macros for Bayesian analysis and Monte Carlo simulations, and detailed appendices in the book guide readers through the use of these software packages. Understanding Computational Bayesian Statistics is an excellent book for courses on computational statistics at the upper-level undergraduate and graduate levels. It is also a valuable reference for researchers and practitioners who use computer programs to conduct statistical analyses of data and solve problems in their everyday work.

Introduction to Bayesian Econometrics

Author : Edward Greenberg
Publisher : Cambridge University Press
ISBN 13 : 1107015316
Total Pages : 271 pages
Book Rating : 4.1/5 (7 download)

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Book Synopsis Introduction to Bayesian Econometrics by : Edward Greenberg

Download or read book Introduction to Bayesian Econometrics written by Edward Greenberg and published by Cambridge University Press. This book was released on 2013 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook explains the basic ideas of subjective probability and shows how subjective probabilities must obey the usual rules of probability to ensure coherency. It defines the likelihood function, prior distributions and posterior distributions. It explains how posterior distributions are the basis for inference and explores their basic properties. Various methods of specifying prior distributions are considered, with special emphasis on subject-matter considerations and exchange ability. The regression model is examined to show how analytical methods may fail in the derivation of marginal posterior distributions. The remainder of the book is concerned with applications of the theory to important models that are used in economics, political science, biostatistics and other applied fields. New to the second edition is a chapter on semiparametric regression and new sections on the ordinal probit, item response, factor analysis, ARCH-GARCH and stochastic volatility models. The new edition also emphasizes the R programming language.

Applied Bayesian Statistics

Author : Mary Kathryn Cowles
Publisher : Springer Science & Business Media
ISBN 13 : 1461456967
Total Pages : 238 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Applied Bayesian Statistics by : Mary Kathryn Cowles

Download or read book Applied Bayesian Statistics written by Mary Kathryn Cowles and published by Springer Science & Business Media. This book was released on 2013-01-04 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is based on over a dozen years teaching a Bayesian Statistics course. The material presented here has been used by students of different levels and disciplines, including advanced undergraduates studying Mathematics and Statistics and students in graduate programs in Statistics, Biostatistics, Engineering, Economics, Marketing, Pharmacy, and Psychology. The goal of the book is to impart the basics of designing and carrying out Bayesian analyses, and interpreting and communicating the results. In addition, readers will learn to use the predominant software for Bayesian model-fitting, R and OpenBUGS. The practical approach this book takes will help students of all levels to build understanding of the concepts and procedures required to answer real questions by performing Bayesian analysis of real data. Topics covered include comparing and contrasting Bayesian and classical methods, specifying hierarchical models, and assessing Markov chain Monte Carlo output. Kate Cowles taught Suzuki piano for many years before going to graduate school in Biostatistics. Her research areas are Bayesian and computational statistics, with application to environmental science. She is on the faculty of Statistics at The University of Iowa.

Handbook Of Applied Econometrics And Statistical Inference

Author : Aman Ullah
Publisher : CRC Press
ISBN 13 : 9780203911075
Total Pages : 754 pages
Book Rating : 4.9/5 (11 download)

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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 754 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summarizing developments and techniques in the field, this reference covers sample surveys, nonparametric analysis, hypothesis testing, time series analysis, Bayesian inference, and distribution theory for applications in statistics, economics, medicine, biology, engineering, sociology, psychology, and information technology. It supplies a geometric proof of an extended Gauss-Markov theorem, approaches for the design and implementation of sample surveys, advances in the theory of Neyman's smooth test, and methods for pre-test and biased estimation. It includes discussions ofsample size requirements for estimation in SUR models, innovative developments in nonparametric models, and more.