The term data snooping, sometimes also referred to as data dredging or data fishing, is used to describe the situation in which a particular data set is analyzed repeatedly without an a priori hypothesis of interest. The practice of data snooping, although common, is problematic because it can result in a significant finding (e.g., rejection of a null hypothesis) that is nothing more than a chance artifact of the repeated analyses of the data. The biases introduced by data snooping increase the more a data set is analyzed in the hope of a significant finding. Empirical research that is based on experimentation and observation has the potential to be impacted by data snooping.

Data Snooping and Multiple Hypothesis Testing

A hypothesis test is conducted at a significance ...

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