This text presents a balanced account of the Bayesian and frequentist approaches to statistical inference. Along with more examples and exercises, this second edition includes new material on empirical Bayes and penalized likelihoods and their impact on regression models and offers expanded material on hypothesis testing, method of moments, bias correction, and hierarchical models. It also compares the Bayesian and frequentist schools of thought and explores procedures that lie on the border between the two.
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