Testing Statistical Hypotheses (Springer Texts in Statistics)
Product Description
Testing Statistical Hypotheses (Springer Texts in Statistics)
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.
Technical Specifications
Customers who bought this also bought
You might also like
Theory of Point Estimation (Springer Texts in Statistics)
Bayesian Data Analysis, Third Edition (Chapman & Hall/CRC Texts in Statistical Science)
Deep Learning (Adaptive Computation and Machine Learning series)
Asymptotic Statistics (Cambridge Series in Statistical and Probabilistic Mathematics)
An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)
The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)
Large-Scale Inference: Empirical Bayes Methods for Estimation, Testing, and Prediction (Institute of Mathematical Statistics Monographs)
Elements of Large-Sample Theory (Springer Texts in Statistics)
Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction
Statistical Decision Theory and Bayesian Analysis (Springer Series in Statistics)