Please use this identifier to cite or link to this item: https://lib.hpu.edu.vn/handle/123456789/22276
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dc.contributor.authorColquhoun, Daviden_US
dc.date.accessioned2016-07-18T06:49:08Z
dc.date.available2016-07-18T06:49:08Z
dc.date.issued2014en_US
dc.identifier.otherHPU4160433en_US
dc.identifier.urihttps://lib.hpu.edu.vn/handle/123456789/22276-
dc.description.abstractIf you use p=0.05 to suggest that you have made a discovery, you will be wrong at least 30% of the time. If, as is often the case, experiments are underpowered, you will be wrong most of the time. This conclusion is demonstrated from several points of view. First, tree diagrams which show the close analogy with the screening test problem. Similar conclusions are drawn by repeated simulations oft-tests.en_US
dc.format.extent16 p.en_US
dc.format.mimetypeapplication/pdf-
dc.language.isoenen_US
dc.subjectStatisticsen_US
dc.subjectComputational biologyen_US
dc.subjectSignificance testsen_US
dc.subjectReproducibilityen_US
dc.subjectStatisticsen_US
dc.subjectFalse discovery raten_US
dc.titleAn investigation of the false discovery rate and the misinterpretation of p-valuesen_US
dc.typeArticleen_US
dc.size741KBen_US
dc.departmentEducationen_US
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