Statement on p-values and statistical significance

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The "Statement on p-values and statistical significance" is a landmark American Statistical Association document that clarifies the proper use and interpretation of p-values and cautions against their misuse in scientific research and decision-making.

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Statements (48)

Predicate Object
instanceOf American Statistical Association statement
guidance document
scientific position statement
accessMode open access
aimsTo clarify proper use of p-values
discourage misuse of p-values
improve statistical practice in science
clarifies a p-value near 0.05 should not be treated as a strict decision rule
p-values do not measure the probability that the data were produced by random chance alone
p-values do not measure the probability that the studied hypothesis is true
statistical significance does not imply scientific or practical importance
countryOfOrigin United States of America
surface form: United States
datePublished 2016
describedAs landmark ASA document on p-values
documentType position paper
emphasizes importance of data quality
importance of full reporting of results
importance of study design
importance of transparency in analysis
field research methodology
statistical inference
statistics
hasPart six principles on the use and interpretation of p-values
influenced debates on reproducibility in science
guidelines for statistical practice in multiple disciplines
journal editorial policies on statistical reporting
language English
mainSubject hypothesis testing
p-value
reproducible research
statistical significance
publisher American Statistical Association NERFINISHED
recommends considering effect sizes
considering prior evidence and plausibility
using confidence intervals
using other measures of evidence
relatedTo ASA special issue on statistical inference in The American Statistician NERFINISHED
discussions on moving beyond p<0.05
targetAudience journal editors
policy makers
scientific researchers
statisticians
warnsAgainst data dredging
mechanical use of bright-line significance thresholds
p-hacking
selective reporting based on p-values
using p-values as a measure of effect size
using p-values as a measure of evidence by themselves

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American Statistical Association notableWork Statement on p-values and statistical significance