p values are calculated as a part of hypothesis testing, and p values indicate the probability of obtaining the difference observed in a random sample or a more extreme one in a population where the null hypothesis is true. Because of the widespread use of hypothesis testing, p values are a part of virtually all quantitative research reports. This entry explains p values in connection to other aspects of hypothesis testing and provides some cautions concerning the use of p values.
Hypothesis testing is one of the main methods used for statistical inference. In hypothesis testing, researchers set up a hypothesis about a population parameter(s) and, based on data from a random sample drawn from this population, test its [Page 1144]tenability. The tested hypothesis is ...
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