p-value

P-value

In <a href="/en/Statistical_hypothesis_testing" title="Statistical hypothesis testing" class="wl">null-hypothesis significance testing</a>, the p-value<a href="#cite_note-2" style="counter-reset: mw-Ref 1;" data-mw-group="note">[note 1]</a> is the probability of obtaining test results at least as extreme as the <a href="/en/Realization_(probability)" title="Realization (probability)" class="wl">result actually observed</a>, under the assumption that the <a href="/en/Null_hypothesis" title="Null hypothesis" class="wl">null hypothesis</a> is correct.<a href="#cite_note-3" style="counter-reset: mw-Ref 2;">[2]</a><a href="#cite_note-ASA-4" style="counter-reset: mw-Ref 3;">[3]</a> A very small p-value means that such an extreme observed <a href="/en/Outcome_(probability)" title="Outcome (probability)" class="wl">outcome</a> would be very unlikely under the null hypothesis. Reporting p-values of statistical tests is common practice in <a href="/en/Academic_publishing" title="Academic publishing" class="wl">academic publications</a> of many quantitative fields. Since the precise meaning of p-value is hard to grasp, <a href="/en/Misuse_of_p-values" title="Misuse of p-values" class="wl">misuse is widespread</a> and has been a major topic in <a href="/en/Metascience" title="Metascience" class="wl">metascience</a>.<a href="#cite_note-5" style="counter-reset: mw-Ref 4;">[4]</a><a href="#cite_note-6" style="counter-reset: mw-Ref 5;">[5]</a>

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<div class="shortdescription nomobile noexcerpt noprint searchaux" style="display:none" about="#mwt5">Function of the observed sample results</div>

In null-hypothesis significance testing, the p-value 