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The most common misinterpretation of the $$p$$ value is mistakenly believing it represents the probability that the null hypothesis is true (i.e., the probability that the result occurred by chance). In reality, the $$p$$ value calculates the probability of obtaining the specific sample data assuming the null hypothesis is already true.

Misinterpretation of the p Value

Which of the following represents the most common misinterpretation of a p value?

A researcher conducts a study comparing two therapy techniques for reducing test anxiety and obtains a p value of .02. She states: 'There is only a 2% chance that the null hypothesis is true.' This is a correct interpretation of the p value.

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