Testing Statistical Hypotheses; Springer Texts in Statistics

Lehmann, Erich L.; Romano, Joseph P.

ISBN 10: 0387988645 / ISBN 13: 9780387988641

Published by Springer, 2005

About this Item

Book has light wear to edges, slight fading to spine, light smudging to textblock edges. Otherwise, attractive copy with clean, unmarked interior.

Seller Inventory # 1046525

Bibliographic Details

• Title: Testing Statistical Hypotheses; Springer Texts in Statistics
• Publisher: Springer
• Publication Date: 2005
• Language: English
• ISBN 10: 0387988645
• ISBN 13: 9780387988641
• Binding: Hardcover
• Edition: Third Edition.
• Condition: Very Good
• Seller catalogs:
  • Mathematics

About this title

Synopsis

The third edition of Testing Statistical Hypotheses updates and expands upon the classic graduate text, emphasizing optimality theory for hypothesis testing and confidence sets. The principal additions include a rigorous treatment of large sample optimality, together with the requisite tools. In addition, an introduction to the theory of resampling methods such as the bootstrap is developed. The sections on multiple testing and goodness of fit testing are expanded. The text is suitable for Ph.D. students in statistics and includes over 300 new problems out of a total of more than 760.

About the Author

E.L. Lehmann is Professor of Statistics Emeritus at the University of California, Berkeley. He is a member of the National Academy of Sciences and the American Academy of Arts and Sciences, and the recipient of honorary degrees from the University of Leiden, The Netherlands and the University of Chicago. He is the author of Elements of Large-Sample Theory and (with George Casella) he is also the author of Theory of Point Estimation, Second Edition.

Joseph P. Romano is Professor of Statistics at Stanford University. He is a recipient of a Presidential Young Investigator Award and a Fellow of the Institute of Mathematical Statistics. He has coauthored two other books, Subsampling with Dimitris Politis and Michael Wolf, and Counterexamples in Probability and Statistics with Andrew Siegel.