Bayesian methods in statistics : from concepts to practice
著者
書誌事項
Bayesian methods in statistics : from concepts to practice
SAGE, 2021
- : pbk
大学図書館所蔵 件 / 全4件
-
該当する所蔵館はありません
- すべての絞り込み条件を解除する
内容説明・目次
内容説明
This book walks you through learning probability and statistics from a Bayesian point of view.
From an introduction to probability theory through to frameworks for doing rigorous calculations of probability, it discusses Bayes' Theorem before illustrating how to use it in a variety of different situations with data addressing social and psychological issues.
The book also:
Equips you with coding skills in the statistical modelling language Stan and programming language R.
Discusses how Bayesian approaches to statistics compare to classical approaches.
Introduces Markov Chain Monte Carlo methods for doing Bayesian statistics through computer simulations, so you understand how Bayesian solutions are implemented.
Features include an introduction to each chapter and a chapter summary to help you check your learning. All the examples and data used in the book are also available in the online resources so you can practice at your own pace.
For readers with some understanding of basic mathematical functions and notation, this book will get you up and running so you can do Bayesian statistics with confidence.
目次
Chapter 1: Probability
Chapter 2: Probability distributions
Chapter 3: Models and inference
Chapter 4: Relationships between variables
Chapter 5: General models
Chapter 6: Questionnaires and non-quantitative responses
Chapter 7: Multiple issues
「Nielsen BookData」 より