<Table> <Tr> <Td> </Td> <Td> This article includes a list of references, but its sources remain unclear because it has insufficient inline citations . Please help to improve this article by introducing more precise citations . (July 2014) (Learn how and when to remove this template message) </Td> </Tr> </Table> <Tr> <Td> </Td> <Td> This article includes a list of references, but its sources remain unclear because it has insufficient inline citations . Please help to improve this article by introducing more precise citations . (July 2014) (Learn how and when to remove this template message) </Td> </Tr> <P> In statistical hypothesis testing, the p - value or probability value is the probability for a given statistical model that, when the null hypothesis is true, the statistical summary (such as the sample mean difference between two compared groups) would be the same as or of greater magnitude than 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 . Their misuse has been a matter of considerable controversy . </P> <P> The p - value is used in the context of null hypothesis testing in order to quantify the idea of statistical significance of evidence . Null hypothesis testing is a reductio ad absurdum argument adapted to statistics . In essence, a claim is assumed valid if its counter-claim is improbable . </P>

What is the p value of the test
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