£88.52

CRC Press Bayesian Statistical Methods - R Code & Data Science

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Description

Master the essential tools for modern data science with Bayesian Statistical Methods from CRC Press. This text provides the foundational and computational knowledge required to perform professional Bayesian analysis. It is designed for practitioners who need to apply these methods to real-world scenarios, including multiple linear regression, mixed effects models, and generalized linear models (GLM). By bridging the gap between theory and practice, this book helps you navigate complex statistical tasks. You will find practical guidance on selecting prior distributions and utilizing computational methods such as Markov chain Monte Carlo. The content is structured to help you understand how Bayesian approaches compare to analogous frequentist procedures, making it a valuable resource for anyone looking to expand their statistical toolkit. Whether you are working on academic research or industry data modeling, this book offers the practical framework needed to implement robust Bayesian workflows.

Key Features

Practical application of Bayesian methods to routine tasks like multiple linear regression, mixed effects models, and generalized linear models (GLM).

Includes many examples with complete R code to help you implement computational methods directly into your data science workflow.

Provides direct comparisons between Bayesian inferential methods and analogous frequentist procedures for a well-rounded statistical understanding.

Offers expert advice on selecting prior distributions to ensure your statistical models are built on a sound foundation.

Covers essential computational topics including Markov chain Monte Carlo methods to support advanced Bayesian analysis.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
16 April 2019
Listed Since
08 January 2019

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