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Wald–Wolfowitz Runs Test: Wald–Wolfowitz Runs Test, Non-parametric Statistics, Statistical Hypothesis Testing, Independence, Probability Theory, Random Variable - Softcover
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Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. 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."
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Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. 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."
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