It is a very decent book for Bayesian theory by Peter Hoff, professor of statistics at UofW. And it does so in a simple manner, always drawing parallels and contrasts between Bayesian and frequentist methods, so as to allow the reader to see the similarities and differences with clarity. £67.81. He is on the editorial board of the Annals of Applied Statistics. Top positive review. Especially . Bayesian Data Analysis (Chapman & Hall/CRC Texts in Statistical Science), Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan, Bayesian Statistics the Fun Way: Understanding Statistics and Probability with Star Wars, LEGO, and Rubber Ducks, Statistical Rethinking: A Bayesian Course with Examples in R and STAN (Chapman & Hall/CRC Texts in Statistical Science), Bayesian Statistics for Beginners: a step-by-step approach, An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics), Beyond Spreadsheets with R: A beginner's guide to R and RStudio, Introduction to Probability, Statistics, and Random Processes, Principles of Statistics (Dover Books on Mathematics). It would be useful add some R code and talk about Bayesian statistics not supposing readers are experienced about the subject. However, familiarity with basic Matrix Algebra and probability is somewhat required. Reviewed in the United States on November 6, 2019. A first course in Bayesian statistical methods. … should appeal to the reader who wants to keep with modern approaches to data analysis.” (Richard P. Heydorn, Technometrics, Vol. It should especially appeal to the reader who has had some statistical courses in estimation and modeling, and wants to understand the Bayesian interpretation of those methods. Physical description ix, 270 p. : ill. ; 25 cm. Nothing to say about the article itself. Extremely overpriced! The author goes beyond a description of the MCMC algorithms, but also provides insight into why the algorithms work. It is definitely not the most advanced book you can find in Bayesian theory but it covers some good topics and gives some good intuition to people who just started to think Bayesian. In my opinion, the biggest advantage of this book is that it provides the reader with a deep understanding of Bayesian procedure concepts rather than purely mathematical formulation. The book includes an ample collection of exercises for all the chapters. Bring your club to Amazon Book Clubs, start a new book club and invite your friends to join, or find a club that’s right for you for free. Your recently viewed items and featured recommendations, Select the department you want to search in. The 13-digit and 10-digit formats both work. 4.0 out of 5 stars Great book; typos only drawback. April 20, 2019. See All Buying Options. In addition, the R code for all the figures is provided on the author's webpage which is another advantage. Other than some minor typos, I cannot think of any noticeable drawbacks which you can also find a list of them on the book's webpage as well. There was an error retrieving your Wish Lists. This is certainly not a good first book in Bayesian methods (maybe a good second book for someone more interested) - especially if you have not taken a course in mathematical statistics, statistical computational methods, or linear algebra (for some chapters). The book is accessible to readers having a basic familiarity with probability, yet allows more advanced readers to quickly grasp the principles underlying Bayesian theory and methods. You're listening to a sample of the Audible audio edition. The text's only main positive for me was the provision of R code to follow along with - and even that uses a very dated notation for R code. Authors: Hoff, Peter D. Free Preview. How are ratings calculated? Emphasis on basic concepts as sets, the probability measure associated with sets, sample space, random variables, information measure, and capacity. Numerous examples with R-code that can be run "as-is" allow the reader to perform the data analyses themselves. R Markdown lecture notes for Peter D. Hoff, "A First Course in Bayesian Statistical Methods", completed as part of a 1-semester independent study course. Add to Wish List. A First Course in Bayesian Statistical Methods @inproceedings{Hoff2009AFC, title={A First Course in Bayesian Statistical Methods}, author={P. Hoff}, year={2009} } P. Hoff; Published 2009; Computer Science; This book provides a compact self-contained introduction to the theory and application of Bayesian statistical methods. Price: $54.99. Are you kidding me? Write a review. 4.0 out of 5 stars Great book; typos only drawback. Also, a "first course in bayesian statistics" as per the preface assumes you have a very solid understanding of fundamentals of probability and statistics (NOT that you know how to use a normal distribution, or other statistical results, you should be familiar with theoretical fundamentals for this book to make sense). Instead, our system considers things like how recent a review is and if the reviewer bought the item on Amazon. Chaos: From Simple Models To Complex Systems (Advances in Statistical Mechanics), Principles of Statistics (Dover Books on Mathematics), Computer Age Statistical Inference (Algorithms, Evidence, and Data Science), Beyond Spreadsheets with R: A beginner's guide to R and RStudio, An Introduction to Information Theory (Dover Books on Mathematics), Introduction to Probability, Statistics, and Random Processes, Principles and Techniques in Combinatorics, Clean Code in Python: Refactor your legacy code base. First course in Bayesian statistical methods. There's a problem loading this menu right now. This book is best for senior undergraduates in statistics or master students in engineering. Buy Monte Carlo Statistical Methods (Springer Texts in Statistics) and by Robert, Christian, Casella, George (ISBN: 9780387212395) from Amazon's Book Store. Fulfillment by Amazon (FBA) is a service we offer sellers that lets them store their products in Amazon's fulfillment centers, and we directly pack, ship, and provide customer service for these products. In order to navigate out of this carousel please use your heading shortcut key to navigate to the next or previous heading. Buy A First Course in Bayesian Statistical Methods (Springer Texts in Statistics) 1st ed. It is a very decent book for Bayesian theory by Peter Hoff, professor of statistics at UofW. Hardcover. Amazon. Nothing to say about the article itself. It would be useful add some R code and talk about Bayesian statistics not supposing readers are experienced about the subject. See all 16 positive reviews › ericw95. Numerous examples from the social, biological and physical sciences show how to implement these methodologies in practice. A First Course in Bayesian Statistical Methods (Springer Texts in Statistics) by Peter D. Hoff. I had to pay $60 for a paperback, and there are still TYPOs in the book? Then you can start reading Kindle books on your smartphone, tablet, or computer - no Kindle device required. Your recently viewed items and featured recommendations, Select the department you want to search in, A First Course in Bayesian Statistical Methods (Springer Texts in Statistics). Also, a "first course in bayesian statistics" as per the preface assumes you have a very solid understanding of fundamentals of probability and statistics (NOT that you know how to use a normal distribution, or other statistical results, you should be familiar with theoretical fundamentals for this book to make sense). The open-source R statistical computing environment provides sufficient functionality to make Monte Carlo estimation very easy for a large number of statistical models and example R-code is provided throughout the text. Too hard for an introduction to the subject. 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