Description 
1 online resource (xiv, 784 pages) 
Series 
Springer texts in statistics 

Springer texts in statistics.

Contents 
The general decision problem  The probability background  Uniformly most powerful tests  Unbiasedness : theory and first applications  Unbiasedness : applications to normal distributions  Invariance  Linear hypotheses  The minimax principle  Multiple testing and simultaneous inference  Conditional inference  Basic large sample theory  Quadratic mean differentiable families  Large sample optimality  Testing goodness of fit  General large sample methods  Appendix : Auxiliary results 
Summary 
"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"Jacket 
Bibliography 
Includes bibliographical references (pages 702756)and indexes 
Notes 
Print version record 
Subject 
Statistical hypothesis testing.

Form 
Electronic book

Author 
Romano, Joseph P., 1960

LC no. 
2004051464 
ISBN 
038727605X 

0387988645 (acidfree paper) 

9780387276052 

9780387988641 (acidfree paper) 
