Unique in its presentation of topics from both classical and Bayesian perspectives, this second edition balances both sides elegantly and describes the relative strengths and weaknesses of the different approaches in each case. It covers all the key topics of standard inference courses, including point and interval estimation, hypothesis testing, prediction, approximation, and linear models. Along with real data examples and exercises for self-study, this edition offers numerous updates that reflect recent developments.