Bayesian Analysis

If you know how to program, you're ready to tackle Bayesian statistics. With this book, you'll learn how to solve statistical problems with Python code instead of mathematical formulas, using discrete probability distributions rather than continuous...

Mathematical Recreations from the Tournament of the Towns contains the complete list of problems and solutions to the International Mathematics Tournament of the Towns from Fall 2007 to Spring 2021.The primary audience for this book is the army of...

A New York Times Book Review Editor's Choice: A vivid account of the generations-long dispute over Bayes' rule, one of the greatest breakthroughs in the history of applied mathematics and statistics "An intellectual romp touching on, among other topics,...

Bayesian statistics is currently undergoing something of a renaissance. At its heart is a method of statistical inference in which Bayes' theorem is used to update the probability for a hypothesis as more evidence or information becomes available. It is...

Supported by a wealth of learning features, exercises, and visual elements as well as online video tutorials and interactive simulations, this book is the first student-focused introduction to Bayesian statistics. Without sacrificing technical...

Developed from celebrated Harvard statistics lectures, Introduction to Probability provides essential language and toolsfor understanding statistics, randomness, and uncertainty. The book explores a wide variety of applications and examples, ranging from...

Statistics lectures have been a source of much bewilderment and frustration for generations of students. This book attempts to remedy the situation by expounding a logical and unified approach to the whole subject of data analysis. This text is...

Handbook of Price Impact Modeling provides practitioners and students with a mathematical framework grounded in academic references to apply price impact models to quantitative trading and portfolio management. Automated trading is now the dominant form...

How do you predict something that has never happened before? There's a useful calculation being employed by Wall Street, Silicon Valley and maths professors all over the world, and it predicts that the human species will become extinct in 760 years...

Based on a well-established and popular course taught by the authors over many years, Stochastic Processes: An Introduction, Third Edition, discusses the modelling and analysis of random experiments, where processes evolve over time. The text begins with...

Bayesian Statistics the Fun Way gets you understanding the theory behind data analysis without making you slog through a load of dry concepts first - with no programming experience necessary. You'll learn about probability with LEGO, statistics through...

Completely updated for a new edition, this book introduces reliability and risks analysis, for both practicing engineers and engineering students at the undergraduate and graduate levels. Since reliability analysis is a multidisciplinary subject, this...

Fundamentals of Mathematical Statistics is meant for a standard one-semester advanced undergraduate or graduate-level course in Mathematical Statistics. It covers all the key topics-statistical models, linear normal models, exponential families,...

The Equation of Knowledge: From Bayes' Rule to a Unified Philosophy of Science introduces readers to the Bayesian approach to science: teasing out the link between probability and knowledge. The author strives to make this book accessible to a very broad...

Winner of the 2016 De Groot Prize from the International Society for Bayesian AnalysisNow 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...

Making good decisions under conditions of uncertainty - which is the norm - requires a sound appreciation of the way random chance works. As analysis and modelling of most aspects of the world, and all measurement, are necessarily imprecise and involve...

Bayesian Modeling and Computation in Python aims to help beginner Bayesian practitioners to become intermediate modelers. It uses a hands on approach with PyMC3, Tensorflow Probability, ArviZ and other libraries focusing on the practice of applied...

Now that people are aware that data can make the difference in an election or a business model, data science as an occupation is gaining ground. But how can you get started working in a wide-ranging, interdisciplinary field that's so clouded in hype?...

There is a logical flaw in the statistical methods used across experimental science. This fault is not a minor academic quibble: it underlies a reproducibility crisis now threatening entire disciplines. In an increasingly statistics-reliant society, this...

Introduction to Stochastic Level Crossing Techniques describes stochastic models and their analysis using the System Point Level Crossing method (abbreviated SPLC or LC). This involves deriving probability density functions (pdfs) or cumulative...

There is a logical flaw in the statistical methods used across experimental science. This fault is not a minor academic quibble: it underlies a reproducibility crisis now threatening entire disciplines. In an increasingly statistics-reliant society, this...

Become more likely to succeed-gain stats mastery with Dummies Statistics: 1001 Practice Problems For Dummies gives you 1,001 opportunities to practice solving problems from all the major topics covered in Statistics classes-in the book and online! Get...

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...

The Baseball Mysteries: Challenging Puzzles for Logical Detectives is a book of baseball puzzles, logical baseball puzzles. To jump in, all you need is logic and a casual fan's knowledge of the game. The puzzles are solved by reasoning from the rules of...

An engaging, sophisticated, and fun introduction to the field of Bayesian statistics, Bayes Rules!: An Introduction to Applied Bayesian Modeling brings the power of modern Bayesian thinking, modeling, and computing to a broad audience. In particular, the...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9780956372840Author James V. StoneFormat PaperbackPage Count 184Imprint James V StonePublisher Sebtel PressWeight(grams) 255gDimensions(mm) 229mm * 152mm *...

Spatial and Spatio-Temporal Bayesian Models with R-INLA provides a much needed, practically oriented & innovative presentation of the combination of Bayesian methodology and spatial statistics. The authors combine an introduction to Bayesian theory and...

This highly acclaimed text, now available in paperback, provides a thorough account of key concepts and theoretical results, with particular emphasis on viewing statistical inference as a special case of decision theory. Information-theoretic concepts...

How do you predict something that has never happened before? There's a useful calculation being employed by Wall Street, Silicon Valley and maths professors all over the world, and it predicts that the human species will become extinct in 760 years...

Bayesian Analysis of Infectious Diseases -COVID-19 and Beyond shows how the Bayesian approach can be used to analyze the evolutionary behavior of infectious diseases, including the coronavirus pandemic. The book describes the foundation of Bayesian...

In the evaluation of healthcare, rigorous methods of quantitative assessment are necessary to establish interventions that are both effective and cost-effective. Usually a single study will not fully address these issues and it is desirable to synthesize...

Cohesively Incorporates Statistical Theory with R ImplementationSince the publication of the popular first edition of this comprehensive textbook, the contributed R packages on CRAN have increased from around 1,000 to over 6,000. Designed for an...

The past decade has seen a dramatic increase in the use of Bayesian methods in marketing due, in part, to computational and modelling breakthroughs, making its implementation ideal for many marketing problems. Bayesian analyses can now be conducted over...

Bayesian Econometrics introduces the reader to the use of Bayesian methods in the field of econometrics at the advanced undergraduate or graduate level. The book is self-contained and does not require that readers have previous training in econometrics...

A comprehensive resource that draws a balance between theory and applications of nonlinear time series analysis Nonlinear Time Series Analysis offers an important guide to both parametric and nonparametric methods, nonlinear state-space models, and...

Bayesian Networks: An Introduction provides a self-contained introduction to the theory and applications of Bayesian networks, a topic of interest and importance for statisticians, computer scientists and those involved in modelling complex data sets...

More Random Walks in Science is an anthology of fascinating and frequently amusing anecdotes, quotations, illustrations, articles, and reviews that reflect the more lighthearted aspects of the scientific world and the less serious excursions of the...

Bayesian methods are increasingly being used in the social sciences, as the problems encountered lend themselves so naturally to the subjective qualities of Bayesian methodology. This book provides an accessible introduction to Bayesian methods, tailored...

Emphasizing fundamental mathematical ideas rather than proofs, Introduction to Stochastic Processes, Second Edition provides quick access to important foundations of probability theory applicable to problems in many fields. Assuming that you have a...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9780486462745Author Andrew H JazwinskiFormat PaperbackPage Count 400Imprint Dover Publications Inc.Publisher Dover Publications Inc.Weight(grams)...