Open AccessScholarly Book Review on Bayesian Statistics for Beginners: A Step-by-Step Approach
Author(s) -
Eahsan Shahriary,
Amir Hajibabaee
Publication year - 2020
Publication title -
asian journal of probability and statistics
Language(s) - English
Resource type - Journals
ISSN - 2582-0230
DOI - 10.9734/ajpas/2020/v9i330226
Subject(s) - markov chain monte carlo , bayesian probability , bayesian statistics , computer science , bayes' theorem , metropolis–hastings algorithm , conjugate prior , probability and statistics , bayesian inference , statistics , mathematics , artificial intelligence
This book offers the students and researchers a unique introduction to Bayesian statistics. Authors provide a wonderful journey in the realm of Bayesian Probability and aspire readers to become Bayesian statisticians. The book starts with Introduction to Probability and covers Bayes’ Theorem, Probability Mass Functions, Probability Density Functions, The Beta-Binomial Conjugate, Markov chain Monte Carlo (MCMC), and Metropolis-Hastings Algorithm. The book is very well written, and topics are very to the point with real-world applications but does not provide examples for computing using common open-source software.