P-vrednost

U statističkom testiranju hipoteze, p-vrednost (engl. probability value) ili vrednost verovatnoće je, za dati statistički model, the probability that, when the null hypothesis is true, the statistical summary (such as the absolute value of the sample mean difference between two compared groups) would be greater than or equal to the actual observed results. The use of p-values in statistical hypothesis testing is common in many fields of research such as physics, economics, finance, political science, psychology, biology, criminal justice, criminology, and sociology. The misuse of p-values is a controversial topic in metascience.

Italicisation, capitalisation and hyphenation of the term varies. For example, AMA style uses "P value", APA style uses "p value", and the American Statistical Association uses "p-value".

Literatura

• Pearson, Karl (1900). „On the criterion that a given system of deviations from the probable in the case of a correlated system of variables is such that it can be reasonably supposed to have arisen from random sampling” (PDF). Philosophical Magazine. Series 5. 50 (302): 157—175. doi:10.1080/14786440009463897. 
• Elderton, William Palin (1902). „Tables for Testing the Goodness of Fit of Theory to Observation”. Biometrika. 1 (2): 155—163. doi:10.1093/biomet/1.2.155. 
• Fisher, Ronald (1925). Statistical Methods for Research Workers. Edinburgh, Scotland: Oliver & Boyd. ISBN 978-0-05-002170-5. 
• Fisher, Ronald A. (1971) [1935]. The Design of Experiments (9th изд.). Macmillan. ISBN 978-0-02-844690-5. 
• Fisher, R. A.; Yates, F. (1938). Statistical tables for biological, agricultural and medical research. London, England. 
• Stigler, Stephen M. (1986). The history of statistics : the measurement of uncertainty before 1900. Cambridge, Mass: Belknap Press of Harvard University Press. ISBN 978-0-674-40340-6. 
• Hubbard, Raymond; Bayarri, M. J. (новембар 2003), P Values are not Error Probabilities (PDF), Архивирано из оригинала (PDF) 2013-09-04. г., a working paper that explains the difference between Fisher's evidential p-value and the Neyman–Pearson Type I error rate α. CS1 одржавање: Формат датума (веза)
• Hubbard, Raymond; Armstrong, J. Scott (2006). „Why We Don't Really Know What Statistical Significance Means: Implications for Educators” (PDF). Journal of Marketing Education. 28 (2): 114—120. doi:10.1177/0273475306288399. Архивирано из оригинала 18. 5. 2006. г. CS1 одржавање: Формат датума (веза)CS1 одржавање: Неподобан URL (веза)
• Hubbard, Raymond; Lindsay, R. Murray (2008). „Why P Values Are Not a Useful Measure of Evidence in Statistical Significance Testing” (PDF). Theory & Psychology. 18 (1): 69—88. doi:10.1177/0959354307086923. 
• Stigler, S. (децембар 2008). „Fisher and the 5% level”. Chance. 21 (4): 12. doi:10.1007/s00144-008-0033-3. CS1 одржавање: Формат датума (веза)
• Dallal, Gerard E. (2012). The Little Handbook of Statistical Practice. 
• Biau, D.J.; Jolles, B.M.; Porcher, R. (март 2010). „P value and the theory of hypothesis testing: an explanation for new researchers”. Clin Orthop Relat Res. 463 (3): 885—892. PMC 2816758 . PMID 19921345. doi:10.1007/s11999-009-1164-4. CS1 одржавање: Формат датума (веза)
• Reinhart, Alex (2015). Statistics Done Wrong: The Woefully Complete Guide. No Starch Press. стр. 176. ISBN 978-1593276201. 

Spoljašnje veze

• Free online p-values calculators for various specific tests (chi-square, Fisher's F-test, etc.).
• Understanding p-values, including a Java applet that illustrates how the numerical values of p-values can give quite misleading impressions about the truth or falsity of the hypothesis under test.
• StatQuest: P Values, clearly explained на сајту YouTube
• StatQuest: P-value pitfalls and power calculations на сајту YouTube