True positive, as it pertains to null hypothesis significance testing (also known as hypothesis testing), is correctly rejecting the null hypothesis when it is in fact false. In other words, it is correctly finding a correlation or a difference between groups. Research design is founded on the principles of hypothesis testing and in short, the pursuit of discovering true positives is a goal. In this entry, the definition of the true positive is developed in the context of null hypothesis significance testing, how it relates to power analysis is described, and an example is provided.

Table 1 Statistical Decision Table: The Four Potential Results with Any Null Hypothesis Significance Test


Null hypothesis significance testing examines the probability of two outcomes (the null and alternative hypothesis). Because ...

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