• Title: Bayesian FreeBook
• Author(s) CRC Authors
• Publisher: CRC Press FREEBOOK
• Paperback: N/A
• eBook: PDF (206 pages)
• Language: English
• ISBN-10/ASIN: N/A
• ISBN-13: N/A
• Share This:  

Book Description

This unique guide will help students develop the statistical confidence and skills to put the Bayesian formula into practice, from the basic concepts of statistical inference to complex applications of analyses.

• An introduction to probability and Bayesian inference
• Understanding Bayes' rule
• Nuts and bolts of Bayesian analytic methods
• Computational Bayes and real-world Bayesian analysis
• Regression analysis and hierarchical methods

• N/A

• Amazon

• Bayesian Thinking
• The R Programming Language
• Statistics, Mathematical Statistics
• Probability and Stochastic
• Data Processing, Data Analysis and Data Mining

• Bayesian FreeBook (CRC)
• The Mirror Site (1) - PDF

• An Introduction to Bayesian Thinking (Merlise Clyde, et al.)

  It provides an introduction to Bayesian Inference in decision making without requiring calculus. It may be used on its own as an open-access introduction to Bayesian inference using R Programming for anyone interested in learning about Bayesian statistics.

• Bayes Rules! An Introduction to Applied Bayesian Modeling

  An engaging, sophisticated, and fun introduction to the field of Bayesian statistics, it brings the power of modern Bayesian thinking, modeling, and computing to a broad audience. Integrates R code, including RStan modeling tools, bayesrules package.

• O'Reilly® Think Bayes: Bayesian Statistics in Python

  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 mathematics.

• Bayesian Models of Perception and Action: An Introduction

  An accessible introduction to constructing and interpreting Bayesian models of perceptual decision-making and action. Provides an approachable introduction to constructing and reasoning with probabilistic models of perceptual decision-making and action.

• Bayesian Models of Cognition: Reverse Engineering the Mind

  How does human intelligence work, in engineering terms? How do our minds get so much from so little? Bayesian models of cognition provide a powerful framework for answering these questions by reverse-engineering the mind.

• Bayesian Data Analysis (Andrew Gelman, et al.)

  This classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. It takes an applied approach to analysis using up-to-date Bayesian methods.

• Bayesian Methods for Hackers: Probabilistic Programming

  This book illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, Matplotlib, through practical examples and computation - no advanced mathematics required.