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In statistics, ''G''-tests are likelihood-ratio or maximum likelihood statistical significance tests that are increasingly being used in situations where chi-squared tests were previously recommended. The general formula for ''G'' is : where ''O''''i'' is the observed frequency in a cell, ''E''''i'' is the expected frequency under the null hypothesis, ln denotes the natural logarithm, and the sum is taken over all non-empty cells. ''G''-tests have been recommended at least since the 1981 edition of the popular statistics textbook by Robert R. Sokal and F. James Rohlf. ==Distribution and usage== Given the null hypothesis that the observed frequencies result from random sampling from a distribution with the given expected frequencies, the distribution of ''G'' is approximately a chi-squared distribution, with the same number of degrees of freedom as in the corresponding chi-squared test. For very small samples the multinomial test for goodness of fit, and Fisher's exact test for contingency tables, or even Bayesian hypothesis selection are preferable to the ''G''-test . 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「G-test」の詳細全文を読む スポンサード リンク
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