| Calling Sequence | StatTest(test,data)
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| Parameters |
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| Return Type | TestStatResult | ||||||||||||
| Synopsis | This function tests several statistical hypothesis. The type of hypothesis to be tested is indicated via the first argument. Tests implemented so far: | ||||||||||||
ChiSquare One-dimensional Chi-square test of independence (cells are assumed equally-probably). "data" is a one-dimensional array of counts (non-negative integers). The data can also be a table or counts which must be indexed over the integers. Every non-zero entry of the table will be assumed an entry in the data. | |||||||||||||
ChiSquare Two-dimensional Chi-square test of independence (rows and columns are assumed independent). "data" is a two-dimensional array of counts (non-negative integers). The data can also be a table of counts which must be indexed over pairs of integers (lists of two integers). Every non-zero entry of the table will be assumed an entry in the data. | |||||||||||||
Independence Two arrays of (any type of) data are grouped to test their independence. The most significant Chi-square test is reported. | |||||||||||||
FriedmanRafsky Tests whether two samples, usually multivariates, come from the same distribution. Each sample must be inputed as a matrix in which each column is a sample. | |||||||||||||
G One-dimensional G test of independence (cells are assumed equally-probably). This is an instance of the likelihood ratio test applied to a list of equiprobable events. "data" is a one-dimensional array of counts (non-negative integers). The data can also be a table or counts which must be indexed over the integers. Every non-zero entry of the table will be assumed an entry in the data. | |||||||||||||
G Two-dimensional G test of independence (rows and columns are assumed independent). This is an instance of the likelihood ratio test applied to tableaux. "data" is a two-dimensional array of counts (non-negative integers). The data can also be a table of counts which must be indexed over pairs of integers (lists of two integers). Every non-zero entry of the table will be assumed an entry in the data. | |||||||||||||
For each hypothesis an internal function will be called that computes the test statistic from the data, the p-value from Cumulative and the standardized deviation from CumulativeStd. | |||||||||||||
| References | HTMLC(Rice JA, Mathematical Statistics and Data Analysis, 2nd ed. chapter 13.4, p.489,Friedman, Rafsky (1979) "Multivariate Generalizations of the Wald-Wolfowitz and Smirnov Two-Sample Tests") | ||||||||||||
| Examples | > StatTest( ChiSquare,[[1,2,3],[4,5,6],[7,8,9]] ); TestStatResult(ChiSquare,0.4688,0.9765,-1.9858,[[1, 2, 3], [4, 5, 6], [7, 8, 9]] ,Degrees_of_freedom = 4) > StatTest( Independence, [A,B,B,B,B,A], [-1,3,4,3,4,-3] ); TestStatResult(ChiSquare,1.5000,0.2207,0.7699,[[2, 0], [2, 2]],Degrees_of_freedom = 1) > StatTest( FriedmanRafsky, [[1,5],[2,-1],[1,3]], [[1,-1],[3,4]] ); TestStatResult(FriedmanRafsky,0.6547,0.5127,0.6547) | ||||||||||||
| See also | Cumulative, CumulativeStd, OutsideBounds, ProbBallsBoxes, ProbCloseMatches, Rand, Std_Score, TestStatResult | ||||||||||||