On the correct interpretation of p values and the importance of random variables.
The p value is the probability under the null hypothesis of obtaining an experimental result that is at least as extreme as the one that we have actually obtained. That probability plays a crucial role in frequentist statistical inferences. But if we take the word 'extreme' to mean 'improbable', the...
| Publicado en: | Synthese Vol. 193; no. 6; pp. 1777 - 1794 |
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| Autor principal: | |
| Formato: | Artículo |
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Springer Nature
Jun2016
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=115247423&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 115247423 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00397857 4LI jtl: Synthese issn: 00397857 maglogo: N pubinfo: dt: Jun2016 vid: 193 iid: 6 pid: 237 pub: Springer Nature artinfo: ui: 115247423 10.1007/s11229-015-0807-0 ppf: 1777 ppct: 17 formats: fmt: @attributes: type: P size: 1009KB tig: atl: On the correct interpretation of p values and the importance of random variables. aug: au: Rochefort-Maranda, Guillaume affil: Département de mathématiques et de statistique, Université Laval, Pavillon Alexandre-Vachon, 1045 Avenue de la Médecine, bureau 1056 Quebec G1V 0A6 Canada su: P-value (Statistics) Statistical significance Random variables Probability theory Mathematical variables sug: subj: P-value (Statistics) Statistical significance Random variables Probability theory Mathematical variables keyword: Frequentist statistics p value Theory testing ab: The p value is the probability under the null hypothesis of obtaining an experimental result that is at least as extreme as the one that we have actually obtained. That probability plays a crucial role in frequentist statistical inferences. But if we take the word 'extreme' to mean 'improbable', then we can show that this type of inference can be very problematic. In this paper, I argue that it is a mistake to make such an interpretation. Under minimal assumptions about the alternative hypothesis, I explain why 'extreme' means 'outside the most precise predicted range of experimental outcomes for a given upper bound probability of error'. Doing so, I rebut recent formulations of recurrent criticisms against the frequentist approach in statistics and underscore the importance of random variables. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Synthese is a copyright of Springer, 2016. All Rights Reserved. item: Synthese holder: Springer Nature dt: @attributes: year: 2016 holdings: @attributes: islocal: N |
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