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InDina [[statisticsstatistik]], the '''nilai-p-value''' oftina avariabel random variable T is thenyaeta [[probability theory|probability]] Pr(T &le; t<sub>observed</sub>) thatnumana T willbakal assumedianggap aleuwih valuegede greateratawa orsarua equaljeung tonilai the observed valueobservasi t<sub>observed</sub>, givendina that akayaan [[null hypothesis]] being considered isdianggap truebener.
 
InDina otherbasa wordssejen, assumeanggapan that a simpleyen null hypothesis is rejectedsederhana ifditolak alamun testtes [[statistic]] ''T'' exceedsleuwih agede criticaltinimbang valuenilai kritis ''c''. SupposeKira-kira thatdina insabagean a particular case thekasus T wasnu observeddi-observasi tosarua be equal tojeung t<sub>observed</sub>. Then theMangka nilai-p-value oftina T indina thateta casekasus isprobabiliti theyen probabilityT that Tbakal wouldsarua equalatawa orleuwih exceedti t<sub>observed</sub>.
 
The p-value does not depend on unobservable parameters, but only on the data, i.e., it is observable; it is a "statistic." In classical frequentist inference, one rejects the null hypothesis if the p-value is smaller than a number called the ''level'' of the test. In effect, the p-value itself is then being used as the test statistic. If the level is 0.05, then the probability that the p-value is less than 0.05, given that the null hypothesis is true, is 0.05, provided the test statistic has a continuous distribution. In that case, the p-value is [[uniform distribution|uniformly distributed]] if the null hypothesis is true.