ðɪ ænˈoʊvə ˈɛftˈɛst ɪz nˈoʊn təbi nˌɪɹli ˈɑːptɪməl ɪnðə sˈɛns ʌv mˈɪnɪmˌaɪzɪŋ fˈɔls nˈɛɡətˌɪv ˈɛɹɚz fɚɹə fˈɪkst ɹˈeɪt ʌv fˈɔls pˈɑːzᵻtˌɪv ˈɛɹɚz ˈaɪ.ˈiː. mˈæksɪmˌaɪzɪŋ pˈaʊɚ fɚɹə fˈɪkst sɪɡnˈɪfɪkəns lˈɛvəl.
The ANOVA F-test is known to be nearly optimal in the sense of minimizing false negative errors for a fixed rate of false positive errors (i.e. maximizing power for a fixed significance level).