define p values. explain the two methods of interpreting p values

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p values. explain the two methods of interpreting p values

In statistical hypothesis testing, the p-value is the probability of obtaining a test statistic at least as extreme as the one that was actually observed, assuming that the null hypothesis is true.
Traditionally, one rejects the null hypothesis if the p-value is less than or equal to the significance level,often represented by the Greek letter a (alpha). (Greek a is also used for Type I error; the connection is that a hypothesis test that rejects the null hypothesis for all samples that have a p-value less than a will have a Type I error of a.) A significance level of 0.05 would deem as extraordinary any result that is within the most extreme 5% of all possible results under the null hypothesis. In this case a p-value less than 0.05 would result in the rejection of the null hypothesis at the 5% (significance) level.

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