A Student s Guide to Bayesian Statistics

A Student   s Guide to Bayesian Statistics

Without sacrificing technical integrity for the sake of simplicity, the author draws upon accessible, student-friendly language to provide approachable instruction perfectly aimed at statistics and Bayesian newcomers.

Author: Ben Lambert

Publisher: SAGE

ISBN: 9781526418289

Category: Mathematics

Page: 521

View: 669

Without sacrificing technical integrity for the sake of simplicity, the author draws upon accessible, student-friendly language to provide approachable instruction perfectly aimed at statistics and Bayesian newcomers.
Categories: Mathematics

Advancements in Bayesian Methods and Implementations

Advancements in Bayesian Methods and Implementations

Bayesian Data Analysis in Ecology Using Linear Models With R, BUGS, and Stan. Academic Press. Lambert, B., 2018. A Student's Guide to Bayesian Statistics. SAGE. Martin, O., 2016. Bayesian Analysis With Python.

Author:

Publisher: Academic Press

ISBN: 9780323952699

Category: Mathematics

Page: 322

View: 626

Advancements in Bayesian Methods and Implementation, Volume 47 in the Handbook of Statistics series, highlights new advances in the field, with this new volume presenting interesting chapters on a variety of timely topics, including Fisher Information, Cramer-Rao and Bayesian Paradigm, Compound beta binomial distribution functions, MCMC for GLMMS, Signal Processing and Bayesian, Mathematical theory of Bayesian statistics where all models are wrong, Machine Learning and Bayesian, Non-parametric Bayes, Bayesian testing, and Data Analysis with humans, Variational inference or Functional horseshoe, Generalized Bayes. Provides the authority and expertise of leading contributors from an international board of authors Presents the latest release in the Handbook of Statistics series Updated release includes the latest information on Advancements in Bayesian Methods and Implementation
Categories: Mathematics

Bayesian Methods for Interaction and Design

Bayesian Methods for Interaction and Design

We also recommend Lambert's A Student's Guide to Bayesian Statistics [34], which has excellent supporting video material. • McGrayne's The Theory that Would Not Die [41] is a very accessible popular science account of the history of ...

Author: John H. Williamson

Publisher: Cambridge University Press

ISBN: 9781108890663

Category: Computers

Page: 374

View: 665

Intended for researchers and practitioners in interaction design, this book shows how Bayesian models can be brought to bear on problems of interface design and user modelling. It introduces and motivates Bayesian modelling and illustrates how powerful these ideas can be in thinking about human-computer interaction, especially in representing and manipulating uncertainty. Bayesian methods are increasingly practical as computational tools to implement them become more widely available, and offer a principled foundation to reason about interaction design. The book opens with a self-contained tutorial on Bayesian concepts and their practical implementation, tailored for the background and needs of interaction designers. The contributed chapters cover the use of Bayesian probabilistic modelling in a diverse set of applications, including improving pointing-based interfaces; efficient text entry using modern language models; advanced interface design using cutting-edge techniques in Bayesian optimisation; and Bayesian approaches to modelling the cognitive processes of users.
Categories: Computers

Introduction to Bayesian Statistics

Introduction to Bayesian Statistics

"...this edition is useful and effective in teaching Bayesian inference at both elementary and intermediate levels.

Author: William M. Bolstad

Publisher: John Wiley & Sons

ISBN: 9781118091562

Category: Mathematics

Page: 617

View: 810

"...this edition is useful and effective in teaching Bayesian inference at both elementary and intermediate levels. It is a well-written book on elementary Bayesian inference, and the material is easily accessible. It is both concise and timely, and provides a good collection of overviews and reviews of important tools used in Bayesian statistical methods." There is a strong upsurge in the use of Bayesian methods in applied statistical analysis, yet most introductory statistics texts only present frequentist methods. Bayesian statistics has many important advantages that students should learn about if they are going into fields where statistics will be used. In this third Edition, four newly-added chapters address topics that reflect the rapid advances in the field of Bayesian statistics. The authors continue to provide a Bayesian treatment of introductory statistical topics, such as scientific data gathering, discrete random variables, robust Bayesian methods, and Bayesian approaches to inference for discrete random variables, binomial proportions, Poisson, and normal means, and simple linear regression. In addition, more advanced topics in the field are presented in four new chapters: Bayesian inference for a normal with unknown mean and variance; Bayesian inference for a Multivariate Normal mean vector; Bayesian inference for the Multiple Linear Regression Model; and Computational Bayesian Statistics including Markov Chain Monte Carlo. The inclusion of these topics will facilitate readers' ability to advance from a minimal understanding of Statistics to the ability to tackle topics in more applied, advanced level books. Minitab macros and R functions are available on the book's related website to assist with chapter exercises. Introduction to Bayesian Statistics, Third Edition also features: Topics including the Joint Likelihood function and inference using independent Jeffreys priors and join conjugate prior The cutting-edge topic of computational Bayesian Statistics in a new chapter, with a unique focus on Markov Chain Monte Carlo methods Exercises throughout the book that have been updated to reflect new applications and the latest software applications Detailed appendices that guide readers through the use of R and Minitab software for Bayesian analysis and Monte Carlo simulations, with all related macros available on the book's website Introduction to Bayesian Statistics, Third Edition is a textbook for upper-undergraduate or first-year graduate level courses on introductory statistics course with a Bayesian emphasis. It can also be used as a reference work for statisticians who require a working knowledge of Bayesian statistics.
Categories: Mathematics

Bayesian Statistics the Fun Way

Bayesian Statistics the Fun Way

Bayesian Statistics the Fun Way will change that. This book will give you a complete understanding of Bayesian statistics through simple explanations and un-boring examples.

Author: Will Kurt

Publisher: No Starch Press

ISBN: 9781593279561

Category: Mathematics

Page: 258

View: 443

Fun guide to learning Bayesian statistics and probability through unusual and illustrative examples. Probability and statistics are increasingly important in a huge range of professions. But many people use data in ways they don't even understand, meaning they aren't getting the most from it. Bayesian Statistics the Fun Way will change that. This book will give you a complete understanding of Bayesian statistics through simple explanations and un-boring examples. Find out the probability of UFOs landing in your garden, how likely Han Solo is to survive a flight through an asteroid shower, how to win an argument about conspiracy theories, and whether a burglary really was a burglary, to name a few examples. By using these off-the-beaten-track examples, the author actually makes learning statistics fun. And you'll learn real skills, like how to: - How to measure your own level of uncertainty in a conclusion or belief - Calculate Bayes theorem and understand what it's useful for - Find the posterior, likelihood, and prior to check the accuracy of your conclusions - Calculate distributions to see the range of your data - Compare hypotheses and draw reliable conclusions from them Next time you find yourself with a sheaf of survey results and no idea what to do with them, turn to Bayesian Statistics the Fun Way to get the most value from your data.
Categories: Mathematics

The Students Guide to Graduate Studies in the UK 1991

The Students  Guide to Graduate Studies in the UK 1991

A Concise Personal Guide to Postgraduate Courses and Research ... and inference ; Bayesian stats , nonlinear time series analysis , computing in stats , multi - d scaling , discrimination , multivariate data analysis , Bayesian game ...

Author:

Publisher:

ISBN: PSU:000017671828

Category: Research

Page: 652

View: 999

Categories: Research

The Students Guide to Graduate Studies in the UK

The Students  Guide to Graduate Studies in the UK

71 : 1 Aberdeen , Mathematics , MSc / PhD See page 341 71 : 2 Aberdeen , Statistics , MSc / PhD ; supervision available ; research interests inc : analysis of repeated measurements in exptl design , theory of inference , Bayesian stats ...

Author:

Publisher:

ISBN: PSU:000010774496

Category: Universities and colleges

Page: 598

View: 632

Categories: Universities and colleges

Experimental Research Methods in Sociolinguistics

Experimental Research Methods in Sociolinguistics

However, it's important to keep in mind that statistical tests are constantly being developed and improved upon. One advantage of working in R is ... In Marianna Di Paolo and Malcah Yaeger-Dror (Eds.) Sociophonetics: A student guide.

Author: Katie Drager

Publisher: Bloomsbury Publishing

ISBN: 9781474251792

Category: Language Arts & Disciplines

Page: 216

View: 788

An accessible, user-friendly guide to the variety of different experimental methods used in sociolinguistics, Experimental Research Methods in Sociolinguistics walks students through the "how-to†? of experimental methods used to investigate variation in both speech production and perception. Focusing squarely on practice and application, it takes the reader from defining a research question, to choosing an appropriate framework, to completing a research project. Featuring a companion website with information on experiment-friendly software, sample experiments and suggestions for work to undertake, the book also covers: -Ethical concerns -How to measure production and perception -How to construct and use corpora
Categories: Language Arts & Disciplines

Bayesian Statistics and Marketing

Bayesian Statistics and Marketing

The book also discusses the theory and practical use of MCMC methods.

Author: Peter E. Rossi

Publisher: John Wiley & Sons

ISBN: 9780470863688

Category: Mathematics

Page: 368

View: 451

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 a wide range of marketing problems, from new product introduction to pricing, and with a wide variety of different data sources. Bayesian Statistics and Marketing describes the basic advantages of the Bayesian approach, detailing the nature of the computational revolution. Examples contained include household and consumer panel data on product purchases and survey data, demand models based on micro-economic theory and random effect models used to pool data among respondents. The book also discusses the theory and practical use of MCMC methods. Written by the leading experts in the field, this unique book: Presents a unified treatment of Bayesian methods in marketing, with common notation and algorithms for estimating the models. Provides a self-contained introduction to Bayesian methods. Includes case studies drawn from the authors’ recent research to illustrate how Bayesian methods can be extended to apply to many important marketing problems. Is accompanied by an R package, bayesm, which implements all of the models and methods in the book and includes many datasets. In addition the book’s website hosts datasets and R code for the case studies. Bayesian Statistics and Marketing provides a platform for researchers in marketing to analyse their data with state-of-the-art methods and develop new models of consumer behaviour. It provides a unified reference for cutting-edge marketing researchers, as well as an invaluable guide to this growing area for both graduate students and professors, alike.
Categories: Mathematics

Bayesian Statistics for Beginners

Bayesian Statistics for Beginners

This is an entry-level book on Bayesian statistics written in a casual, and conversational tone.

Author: Therese M. Donovan

Publisher: Oxford University Press, USA

ISBN: 0198841302

Category: Bayesian statistical decision theory

Page: 419

View: 111

This is an entry-level book on Bayesian statistics written in a casual, and conversational tone. The authors walk a reader through many sample problems step-by-step to provide those with little background in math or statistics with the vocabulary, notation, and understanding of the calculations used in many Bayesian problems.
Categories: Bayesian statistical decision theory