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- Data_dredging abstract "Data dredging (data fishing, data snooping, equation fitting) is the use of data mining to uncover relationships in data.The process of data mining involves automatically testing huge numbers of hypotheses about a single data set by exhaustively searching for combinations of variables that might show a correlation. Conventional tests of statistical significance are based on the probability that an observation arose by chance, and necessarily accept some risk of mistaken test results, called the significance. When large numbers of tests are performed, some produce false results, hence 5% of randomly chosen hypotheses turn out to be significant at the 5% level, 1% turn out to be significant at the 1% significance level, and so on, by chance alone. When enough hypotheses are tested, it is virtually certain that some falsely appear statistically significant, since almost every data set with any degree of randomness is likely to contain some spurious correlations. If they are not cautious, researchers using data mining techniques can be easily misled by these apparently significant results.The multiple comparisons hazard is common in data dredging. Moreover, subgroups are sometimes explored without alerting the reader to the number of questions at issue, which can lead to misinformed conclusions.Circumventing the traditional scientific approach by conducting an experiment without a hypothesis can lead to premature conclusions.".
- Data_dredging wikiPageExternalLink data-snooping.martinsewell.com.
- Data_dredging wikiPageExternalLink info%3Adoi%2F10.1371%2Fjournal.pmed.0020124.
- Data_dredging wikiPageID "1311951".
- Data_dredging wikiPageRevisionID "584745094".
- Data_dredging hasPhotoCollection Data_dredging.
- Data_dredging subject Category:Bias.
- Data_dredging subject Category:Cognitive_biases.
- Data_dredging subject Category:Data_mining.
- Data_dredging subject Category:Design_of_experiments.
- Data_dredging subject Category:Hypothesis_testing.
- Data_dredging subject Category:Misuse_of_statistics.
- Data_dredging type Abstraction100002137.
- Data_dredging type Attitude106193203.
- Data_dredging type Bias106201908.
- Data_dredging type Cognition100023271.
- Data_dredging type CognitiveBiases.
- Data_dredging type Inclination106196584.
- Data_dredging type Partiality106201136.
- Data_dredging type PsychologicalFeature100023100.
- Data_dredging comment "Data dredging (data fishing, data snooping, equation fitting) is the use of data mining to uncover relationships in data.The process of data mining involves automatically testing huge numbers of hypotheses about a single data set by exhaustively searching for combinations of variables that might show a correlation.".
- Data_dredging label "Data dredging".
- Data_dredging sameAs m.04r_99.
- Data_dredging sameAs Q5227277.
- Data_dredging sameAs Q5227277.
- Data_dredging sameAs Data_dredging.
- Data_dredging wasDerivedFrom Data_dredging?oldid=584745094.
- Data_dredging isPrimaryTopicOf Data_dredging.