High Quality Content by WIKIPEDIA articles! High Quality Content by WIKIPEDIA articles! In statistics, data-snooping bias is a form of statistical bias generated by the misuse of data mining techniques that can lead to bogus results in scientific research. Although data-snooping biases can occur in any field that uses data mining, data snooping biases are a particular concern in finance and medical research, both of which make heavy use of data mining techniques. In the process of data mining, huge numbers of hypotheses about a single data set can be tested in a very short time, by exhaustively searching for combinations of variables that might show a correlation. Because conventional tests of statistical significance are based on the probability that an observation arose by chance, it is reasonable to expect that 5% of randomly chosen hypotheses will turn out to be significant at the 5% level, 0.1% will turn out to be significant at the 0.1% significance level, and so on, simply by chance.

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