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...

The International Bestseller by 'The Galileo of number crunchers' (Independent)Every time we choose a route to work, decide whether to go on a second date, or set aside money for a rainy day, we are making a prediction about the future. Yet from the...

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...

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?...

Updated to conform to Mathematica (R) 7.0, Introduction to Probability with Mathematica (R), Second Edition continues to show students how to easily create simulations from templates and solve problems using Mathematica. It provides a real understanding...

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 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...

Spatial point processes play a fundamental role in spatial statistics and today they are an active area of research with many new applications. Although other published works address different aspects of spatial point processes, most of the classical...

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...

Praise for the Second Edition:"The author has done his homework on the statistical tools needed for the particular challenges computer scientists encounter... [He] has taken great care to select examples that are interesting and practical for computer...

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...

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...

Praise for the first edition: Principles of Uncertainty is a profound and mesmerising book on the foundations and principles of subjectivist or behaviouristic Bayesian analysis. ... the book is a pleasure to read. And highly recommended for teaching as...

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...

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...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9780956372895Author James V. StoneFormat PaperbackPage Count 186Imprint Sebtel PressPublisher Sebtel Press

Learn the fundamentals of Bayesian modeling using state-of-the-art Python libraries, such as PyMC, ArviZ, Bambi, and more, guided by an experienced Bayesian modeler who contributes to these libraries Key Features Conduct Bayesian data analysis with...

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...

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...

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...

Probability and Statistical Inference: From Basic Principles to Advanced Models covers aspects of probability, distribution theory, and inference that are fundamental to a proper understanding of data analysis and statistical modelling. It presents these...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9780993367908Author J.V. StoneFormat PaperbackPage Count 260Imprint Sebtel PressPublisher Sebtel Press

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...

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...

Bayesian Analysis with Stata is written for anyone interested in applying Bayesian methods to real data easily. The book shows how modern analyses based on Markov chain Monte Carlo (MCMC) methods are implemented in Stata both directly and by passing...

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 book provides a comprehensive and concrete illustration of time series analysis focusing on the state-space model, which has recently attracted increasing attention in a broad range of fields. The major feature of the book lies in its consistent...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9780993367946Author Dr James V StoneFormat PaperbackPage Count 186Imprint Sebtel PressPublisher Sebtel PressWeight(grams) 258g

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...

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 9781948255929Author Origins PublicationsFormat PaperbackPage Count 100Imprint Origins PublicationsPublisher Origins PublicationsWeight(grams)...

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...

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...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9780993367939Author Dr James V StoneFormat PaperbackPage Count 188Imprint Sebtel PressPublisher Sebtel PressWeight(grams) 259g

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...

Applied sciences, both physical and social, such as atmospheric, biological, climate, demographic, economic, ecological, environmental, oceanic and political, routinely gather large volumes of spatial and spatio-temporal data in order to make wide...

These lecture notes provide a rapid, accessible introduction to Bayesian statistical methods. The course covers the fundamental philosophy and principles of Bayesian inference, including the reasoning behind the prior/likelihood model construction...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9781923045866Author Andrew HintonFormat PaperbackPage Count 158Imprint Book Bound StudiosPublisher Book Bound StudiosWeight(grams) 218g

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 *...

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...