Overview
- Develops the foundations, principles, theory, and methods of hypothesis testing
- Offers new coverage of multiple hypothesis testing, high-dimensional testing, permutation, and more
- Features over 100 new problems, bringing the total to approximately 900 problems across both volumes.
Part of the book series: Springer Texts in Statistics (STS)
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Table of contents (18 chapters)
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Front Matter
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Conditional Inference
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Front Matter
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Keywords
About this book
Testing Statistical Hypotheses, 4th Edition updates and expands upon the classic graduate text, now a two-volume work. The first volume covers finite-sample theory, while the second volume discusses large-sample theory. A definitive resource for graduate students and researchers alike, this work grows to include new topics of current relevance. New additions include an expanded treatment of multiple hypothesis testing, a new section on extensions of the Central Limit Theorem, coverage of high-dimensional testing, expanded discussions of permutation and randomization tests, coverage of testing moment inequalities, and many new problems throughout the text.
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Authors and Affiliations
About the authors
E.L. Lehmann (1917 – 2009) was an American statistician and professor of statistics at the University of California, Berkeley. He made significant contributions to nonparametric hypothesis testing, and he is one of the eponyms of the Lehmann-Scheffé theorem and of the Hodges-Lehmann estimator. Dr. Lehmann was 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 was the author of Elements of Large-Sample Theory (Springer 1999) and Theory of Point Estimation, Second Edition (Springer 1998, with George Casella).
Joseph P. Romano has been on faculty in the Statistics Department at Stanford since 1986. Since 2007, he has held a joint professorship appointment in both Statistics and Economics. He is a coauthor of three books, as well as over 100 journal articles. Dr. Romano was named NOGLSTP's 2021 LGBTQ+ Scientist of the Year, has been a recipient of the Presidential Young Investigator Award and many other grants from the National Science Foundation, and is a Fellow of the Institute of Mathematical Statistics and of the International Association of Applied Econometrics. His research has focused on such topics as: bootstrap and resampling methods, subsampling, randomization methods, inference, optimality, large-sample theory, nonparametrics, multiple hypothesis testing, and econometrics. He has invented or co-invented a variety of new statistical methods, including subsampling and the stationary bootstrap, as well as methods for multiple hypothesis testing. These methods have been applied to such diverse fields as clinical trials, climate change, finance, and economics.
Bibliographic Information
Book Title: Testing Statistical Hypotheses
Authors: E.L. Lehmann, Joseph P. Romano
Series Title: Springer Texts in Statistics
DOI: https://doi.org/10.1007/978-3-030-70578-7
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022
Hardcover ISBN: 978-3-030-70577-0Published: 24 June 2022
Softcover ISBN: 978-3-030-70580-0Published: 25 June 2023
eBook ISBN: 978-3-030-70578-7Published: 22 June 2022
Series ISSN: 1431-875X
Series E-ISSN: 2197-4136
Edition Number: 4
Number of Pages: XV, 1012
Number of Illustrations: 6 b/w illustrations, 7 illustrations in colour
Topics: Statistical Theory and Methods, Probability Theory and Stochastic Processes, Statistics, general