The second edition of a well-received book that was published 24 years ago and continues to sell to this day, An Introduction to Probability and Statistics is now revised to ...

Probability; Random variables and their probability distributions; Moments and generating functions; Random vectors; Some special distributions; Limit theorems; Sample moments ...

Minimum-variance unbiased estimation; The method of least squares; The method of maximum likelihood; Confidence sets; Hypothesis testing; The likelihood-ratio test and ...

This book offers a modern approach to statistical inference with more information on ancillarity, invariance, Bayesian methods, pivots, Stein estimation, errors in variables ...

Statistical inference is the foundation on which much of statistical practice is built. This book covers the topic at a level suitable for students and professionals who need ...

A comprehensive, self-contained, yet easily accessible presentation of basic concepts, examining measure-theoretic foundations as well as analytical tools. Covers classical as ...

This modern treatment of mathematical statistics is concise, yet detailed enough to give readers a solid foundation in all aspects of the field. Treatment of each topic is ...

This classic, time-honored introduction to the theory and practice of statistics modeling and inference reflects the changing focus of contemporary Statistics. Coverage begins ...

Relevant, concrete, and thorough--the essential data-based text on statistical inference The ability to formulate abstract concepts and draw conclusions from data is ...