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.
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