Behrens-Fisher problem


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Behrens-Fisher problem

[¦ber·ənz ¦fish·ər ‚präb·ləm]
(statistics)
The problem of calculating the probability of drawing two random samples whose means differ by some specified value (which may be zero) from normal populations, when one knows the difference of the means of these populations but not the ratio of their variances.
References in periodicals archive ?
This is the well-known Behrens-Fisher problem in statistics [4, 5], which we will not discuss here.
A revisit to the Behrens-Fisher problem: Comparison of ve test meth-ods.
This problem is analogous to the Behrens-Fisher problem; see, for example, Tang and Tsui [12] and Somkhuean et al.
Moreover, Tsui and Weerahandi [10] used the generalized p value p(x) for the Behrens-Fisher problem of testing the difference of two independent normal distribution means with possibly unequal variances.
We note here that the results for these results for case (1), case (2), and case (3) were analogous to the upper bound of the generalized p value for the Behrens-Fisher problem proposed by Tang and Tsui [12].
Robust rank procedures for the Behrens-Fisher problem. Journal of the American Statistical Association 76:162-168.
Probabilities of the Type I errors of the Welch tests for the Behrens-Fisher problem. Journal of the American Statistical Association 66:605-608.
The rank transformation approach to analysis of variance (ANOVA) as a solution to the Behrens-Fisher problem was examined.