P-value

The P-value or probability value is a statistical concept that measures the strength of evidence in support of a scientific theory. It is defined as the probability of obtaining a result equal to or "more extreme" than what was actually observed, assuming that the null hypothesis is true.

Definition

The P-value is used in the context of a null hypothesis testing procedure to quantify the idea of statistical significance of evidence. The null hypothesis is the default assumption that there is no relationship between two measured phenomena.

Interpretation

The P-value is not the probability that the null hypothesis is true, nor is it the probability that the alternative hypothesis is false. It is the probability of observing a result at least as extreme as the one that was actually observed, assuming that the null hypothesis is true.

Misunderstandings

There are common misunderstandings about the P-value, such as the belief that it is the probability that the observed data were produced by random chance alone. This is not true; the P-value is conditioned on the null hypothesis being true, and hence, it is a measure of compatibility between the observed data and what we would predict or expect to see if the null hypothesis were true.

See also

• Statistical significance
• Null hypothesis
• Type I and type II errors
• Statistical hypothesis testing

References

• 
  Portrait of John Arbuthnot
• 
  Portrait of Pierre-Simon Laplace
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  Page from the Journal of Heredity
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  Young Ronald Fisher