Another solution to the problem of data dredging is to use the Bonferroni correction. It is now common practice to register clinical trials and specify in advance what the primary endpoints and hypotheses are to avoid the bias of data dredging. They may not be a true relationship and is spurious and any correlation found is by chance.ĭata dredging is also referred to as fishing, p-hacking, significance chasing or data snooping. If you do many and repeated statistical tests (multiple comparisons) on a data set, then some will be statistically significant by chance. This typically happens when a data set is examined too many times with many statistical tests on the data and then only reporting or paying attention to those results that come back with statistical significance. This leads to a spurious excess of false-positive and statistically significant results. Data mining is a technical term that describes the process of combing through massive amounts of data to retrieve both related and unrelated information based. Data dredging is the cherry-picking of multiple statistical tests on a data set to demonstrate a promising or attractive finding.
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