Hypothesis Testing
Neyman–Pearson, likelihood ratio, and uniformly most powerful tests.
Hypothesis Testing. Neyman–Pearson, likelihood ratio, and uniformly most powerful tests. This page collects canonical references that organise the subject and provide entry points to its main techniques.
Foundations and canonical references
The standard treatments of hypothesis testing approach the subject from complementary angles. Lehmann, Testing Statistical Hypotheses (2005) is the anchor reference for the subject and lays out the core definitions, theorems, and worked examples that practitioners return to.
Open methodological questions for hypothesis testing include sharpening the bridges between foundational theory and computational practice, extending classical results to broader or more structured settings, and integrating the techniques surveyed above with adjacent mathematical disciplines. The references listed in this page are the entry points that current work builds on.
Prerequisites
Sources
- textbook · primary · 2005Testing Statistical Hypotheseslehmann-2005, romano-2005
In context
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