As someone whose frequentist attitude in probability theory was always the prior idea of the field, I felt a need to challenge my current understanding with the Bayesian calculations. MCMC (Markov Chain Monte Carlo), playing poker and the books I have been recently reading and my own data analysis have all been the trigger to start challenging my ideas in probability.

This book is a great introduction to Bayesian probability theory. It provides a solid foundation for understanding the principles and applications of Bayesian methods. The author presents complex concepts in a clear and accessible manner, making it suitable for both beginners and those with some background in probability.

The main theme of the book is probability theory as extended logic.

The new perception amounts to the recognition that the mathematical rules of probability theory are not merely rules for calculating frequencies of "random variables"; they are also the unique consistent rules for conducting inference of any kind and we all shall apply them in full generality to that end.