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Wald Wolfowitz Runs Test
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High Quality Content by WIKIPEDIA articles! The runs test also called Wald Wolfowitz test is a non-parametric statistical test that checks a randomness hypothesis for a two-valued data sequence. More precisely, it can be used to test the hypothesis that the elements of the sequence are mutually independent. A "run" of a sequence is a maximal non-empty segment of the sequence consisting of adjacent equal elements. These parameters do not depend on the "fairness" of the process generating the elements of the sequence in the sense that +'s and 's must have equal probabilities, but only on the assumption that the elements are independent and identically distributed. If there are too many runs more or less than expected, the hypothesis of statistical independence of the elements may be rejected.
Klappentext
High Quality Content by WIKIPEDIA articles! The runs test also called Wald-Wolfowitz test is a non-parametric statistical test that checks a randomness hypothesis for a two-valued data sequence. More precisely, it can be used to test the hypothesis that the elements of the sequence are mutually independent. A "run" of a sequence is a maximal non-empty segment of the sequence consisting of adjacent equal elements. These parameters do not depend on the "fairness" of the process generating the elements of the sequence in the sense that +'s and -'s must have equal probabilities, but only on the assumption that the elements are independent and identically distributed. If there are too many runs more or less than expected, the hypothesis of statistical independence of the elements may be rejected.
Weitere Informationen
- Allgemeine Informationen
- GTIN 09786130334307
- Editor Lambert M. Surhone, Miriam T. Timpledon, Susan F. Marseken
- Sprache Englisch
- Größe H220mm x B150mm x T5mm
- Jahr 2010
- EAN 9786130334307
- Format Kartonierter Einband
- ISBN 978-613-0-33430-7
- Titel Wald Wolfowitz Runs Test
- Untertitel Wald-Wolfowitz Runs Test, Non-parametric Statistics, Statistical Hypothesis Testing, Independence, Probability Theory, Random Variable
- Gewicht 130g
- Herausgeber Betascript Publishers
- Anzahl Seiten 76
- Genre Mathematik