This is an introduction to Bayesian statistics and decision theory, including advanced topics such as Monte Carlo methods. This new edition contains several revised chapters and a new chapter on model choice.

This is an introduction to Bayesian statistics and decision theory, including advanced topics such as Monte Carlo methods. This new edition contains several revised chapters and a new chapter on model choice.

This is an introduction to Bayesian statistics and decision theory, including advanced topics such as Monte Carlo methods. This new edition contains several revised chapters and a new chapter on model choice.

This is an introduction to Bayesian statistics and decision theory, including advanced topics such as Monte Carlo methods. This new edition contains several revised chapters and a new chapter on model choice.

#1 New York Times bestseller Nicholas Sparks turns his unrivaled talents to a new tale about love found and lost, and the choices we hope we'll never have to make. Travis Parker has everything a man could want: a good job, loyal friends, even a waterfront home in small-town North Carolina. In full pursuit of the good life - boating, swimming , and regular barbecues with his ...(展开全部)

Travis Parker has everything a man could want: a good job; loyal friends; his dream home in small-town North Carolina. In full pursuit of the good life, he believes that a serious relationship with a woman would only cramp his style. That is until Gabby Holland moves in next door. Despite Travis's attempts to be friendly, she seems to have a chip on her shoulder about him. But ...(展开全部)

In this clearly reasoned defense of Bayes's Theorem — that probability can be used to reasonably justify scientific theories — Colin Howson and Peter Urbach examine the way in which scientists appeal to probability arguments, and demonstrate that the classical approach to statistical inference is full of flaws. Arguing the case for the Bayesian method with little more than basi...(展开全部)

In this clearly reasoned defense of Bayes's Theorem — that probability can be used to reasonably justify scientific theories — Colin Howson and Peter Urbach examine the way in which scientists appeal to probability arguments, and demonstrate that the classical approach to statistical inference is full of flaws. Arguing the case for the Bayesian method with little more than basi...(展开全部)