Data dredging (also known as data snooping or p-hacking) [1][a] is the misuse of data analysis to find patterns in data that can be presented as statistically significant, thus Data dredging (or data fishing, snooping, or p-hacking) refers to purposely exploring different data subsets or doing multiple statistical tests until a significant
Data dredging is defined as “cherry-picking of promising findings leading to a spurious excess of statistically significant results in published or unpublished literature”. Data fishing (or data dredging) poses an existential threat to the integrity of data decision making because it ignores the principle of representative samples and
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