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Testing Statistical Hypotheses /

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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 gr...

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Bibliographic Details
Main Authors: Lehmann, E.L (Author), Romano, Joseph P. (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2022.
Edition:4th ed. 2022.
Series:Springer Texts in Statistics,
Subjects:
Statistics .
Probabilities.
Statistical Theory and Methods.
Probability Theory.
Statistics.
Electronic books.
Online Access:Connect to the full text of this electronic book
Table of Contents:
  • 1. The General Decision Problem
  • 2. The Probability Background
  • 3. Uniformly Most Powerful Tests
  • 4. Unbiasedness: Theory and First Applications
  • 5. Unbiasedness: Applications to Normal Distributions
  • 6. Invariance
  • 7. Linear Hypotheses
  • 8. The Minimax Principle
  • 9. Multiple Testing and Simultaneous Inference
  • 10. Conditional Inference
  • 11. Basic Large Sample Theory
  • 12. Extensions of the CLT to Sums of Dependent Random Variables
  • 13. Applications to Inference
  • 14. Quadratic Mean Differentiable Families
  • 15. Large Sample Optimality
  • 16. Testing Goodness of Fit
  • 17. Permutation and Randomization Tests
  • 18. Bootstrap and Subsampling Methods
  • A. Auxiliary Results.