pDesigned for a one-semester advanced undergraduate or graduate statistical theory course, istrongStatistical Theory A Concise Introduction, Second Edition strongiclearly explains the underlying ideas, mathematics, and principles of major statistical concepts, including parameter estimation, confidence intervals, hypothesis testing, asymptotic analysis, Bayesian inference, linear models, nonparametric statistics, and elements of decision theory. It introduces these topics on a clear intuitive level using illustrative examples in addition to the formal definitions, theorems, and proofs.ppBased on the authors' lecture notes, the book is self-contained, which maintains a proper balance between the clarity and rigor of exposition. In a few cases, the authors present a sketched version of a proof, explaining its main ideas rather than giving detailed technical mathematical and probabilistic arguments. ppFeatures pul p p liSecond edition has been updated with a new chapter on iNonparametric