Ajén-P: Béda antarrépisi
Konten dihapus Konten ditambahkan
m bot Miceun: fa:پی - مقدار (strong connection between (2) su:Ajén-P and fa:پی-مقدار) |
m Ngarapihkeun éjahan, replaced: nyaeta → nyaéta, yen → yén (2), ea → éa using AWB |
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Dina [[statistik]], '''nilai-p''' tina variabel random T |
Dina [[statistik]], '''nilai-p''' tina variabel random T nyaéta [[téori probabilitas|probabilitas]] Pr(T ≤ t<sub>observed</sub>) numana T bakal dianggap leuwih gede atawa sarua jeung nilai observasi t<sub>observed</sub>, dina kayaan [[null hypothesis]] dianggap bener. |
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Dina basa sejen, anggapan |
Dina basa sejen, anggapan yén null hypothesis sederhana ditolak lamun tes [[statistic]] ''T'' leuwih gede tinimbang nilai kritis ''c''. Kira-kira dina sabagéan kasus T nu di-observasi sarua jeung t<sub>observed</sub>. Mangka nilai-p tina T dina éta kasus probabiliti yén T bakal sarua atawa leuwih ti t<sub>observed</sub>. |
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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 [[sebaran seragam|uniformly distributed]] if the null hypothesis is true. |
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 [[sebaran seragam|uniformly distributed]] if the null hypothesis is true. |
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==Frequent misunderstandings== |
==Frequent misunderstandings== |
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There are several common misunderstandings about p-values. All of the following statements are '''FALSE''': |
There are several common misunderstandings about p-values. All of the following statements are '''FALSE''': |
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a) The p-value is the probability that the [[null hypothesis]] is true, justifying the "rule" of considering as significant p-values closer to 0 (zero). |
a) The p-value is the probability that the [[null hypothesis]] is true, justifying the "rule" of considering as significant p-values closer to 0 (zero). |
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Comment: In fact, [[frequentism|frequentist statistics]] does not, and cannot, attach probabilities to hypotheses. Comparison of Bayesian and classical approaches shows that p can be very close to zero while the posterior probability of the null is very close to unity. This is the '''Jeffreys-Lindley Paradox'''. |
Comment: In fact, [[frequentism|frequentist statistics]] does not, and cannot, attach probabilities to hypotheses. Comparison of Bayesian and classical approaches shows that p can be very close to zero while the posterior probability of the null is very close to unity. This is the '''Jeffreys-Lindley Paradox'''. |
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== Sumber Rujukan == |
== Sumber Rujukan == |
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* Sellke, T., M.J. Bayarri, & J. Berger. 2001. Calibration of P-values for Testing Precise Null Hypotheses. ''Am. Statistician'' 55: 62-71. |
* Sellke, T., M.J. Bayarri, & J. Berger. 2001. Calibration of P-values for Testing Precise Null Hypotheses. ''Am. Statistician'' 55: 62-71. |
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Révisi nurutkeun 21 Désémber 2016 04.20
Dina statistik, nilai-p tina variabel random T nyaéta probabilitas Pr(T ≤ tobserved) numana T bakal dianggap leuwih gede atawa sarua jeung nilai observasi tobserved, dina kayaan null hypothesis dianggap bener.
Dina basa sejen, anggapan yén null hypothesis sederhana ditolak lamun tes statistic T leuwih gede tinimbang nilai kritis c. Kira-kira dina sabagéan kasus T nu di-observasi sarua jeung tobserved. Mangka nilai-p tina T dina éta kasus probabiliti yén T bakal sarua atawa leuwih ti tobserved.
Sumber Rujukan
- Sellke, T., M.J. Bayarri, & J. Berger. 2001. Calibration of P-values for Testing Precise Null Hypotheses. Am. Statistician 55: 62-71.
Artikel ieu mangrupa taratas, perlu disampurnakeun. Upami sadérék uninga langkung paos perkawis ieu, dihaturan kanggo ngalengkepan. |