Abstract
A statistical hypothesis is a statement about one or more population parameter(s). A hypothesis test is a rule for deciding which of two complementary hypotheses is true, based on some data. Various methods for constructing hypothesis tests (e.g., likelihood, Bayesian, intersection-union) are available. Various measures for evaluating hypothesis tests, most of which are related to the tests' probabilities of making correct or incorrect decisions, are available, also. Construction and evaluation of tests, if a large sample is available, is sometimes simplified by asymptotic results.
| Original language | English (US) |
|---|---|
| Title of host publication | International Encyclopedia of the Social & Behavioral Sciences: Second Edition |
| Publisher | Elsevier Inc. |
| Pages | 491-493 |
| Number of pages | 3 |
| ISBN (Electronic) | 9780080970875 |
| ISBN (Print) | 9780080970868 |
| DOIs | |
| State | Published - Mar 26 2015 |
| Externally published | Yes |
Keywords
- Acceptance region
- Alternative hypothesis
- Bayesian
- Intersection-union
- Level
- Likelihood ratio
- Null hypothesis
- P-value
- Power
- Rejection region
- Score test
- Size
- Type I error
- Type II error
- Union-intersection
- Wald test
ASJC Scopus subject areas
- General Social Sciences