假設一個多變量常態母體，要檢定其平均數是否等價之檢定統計量所利用的概念是：各母體平均數和所有母體的總平均數之間的最大距離會小於一個很微量的值。當虛無假設為真時，檢定量落在拒絕區域內的機率稱之為檢定水準。本研究討論在虛無假設成立下，達到最大檢定水準之均數組合，稱為最大水準均數組合。在均數組合下，檢定水準和檢定力是與未知的平均數和變異數完全獨立的。因此，一旦虛無假設已設定，就可同時求出該假設檢定量之p值。本研究探討四類不同性質的股票基金，根據已知條件，利用電腦程式求出該假設檢定量之p值，也就是各公司間沒有差異的最低標準。附上計算p值統計表的電腦程式。

Assuming a multivariate normal distribution, a distance test statistic is proposed to test the hypothesis of equivalence of normal means, where the equivalence is defined to be maximum distance of treatment means from the grand mean being falling into a small but negligible zone. The least favorable mean configuration (LFMC) to guarantee the maximum level at a null hypothesis is investigated. These level (and the power) of the test are fully independent of the unknown means and variances. For a given null hypothesis,the p-value of the test for an experiment can be determined. Statistical tables of critical values and computer program for evaluating the p-value are provided.

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