fɔːɹ ɛɡzˈæmpəl, tə tˈɛst ðə haɪpˈɑːθəsˌɪs ðæt vˈɛɹiəs mˈɛdɪkəl tɹˈiːtmənts hæv ɛɡzˈæktli ðə sˈeɪm ɪfˈɛkt, ðɪ ˈɛftˈɛsts pˈiːvˈæljuːz klˈoʊsli ɐpɹˈɑːksɪmˌeɪt ðə pˌɜːmjuːtˈeɪʃən tˈɛsts pˈiːvˈæljuːz: ðɪ ɐpɹˌɑːksɪmˈeɪʃən ɪz pɚtˈɪkjʊlɚli klˈoʊs wɛn ðə dɪzˈaɪn ɪz bˈælənst.
For example, to test the hypothesis that various medical treatments have exactly the same effect, the F-test's p-values closely approximate the permutation test's p-values: The approximation is particularly close when the design is balanced.