Multiple comparisons | Statistical hypothesis testing

Multiple comparisons problem

In statistics, the multiple comparisons, multiplicity or multiple testing problem occurs when one considers a set of statistical inferences simultaneously or infers a subset of parameters selected based on the observed values. The more inferences are made, the more likely erroneous inferences become. Several statistical techniques have been developed to address that problem, typically by requiring a stricter significance threshold for individual comparisons, so as to compensate for the number of inferences being made. (Wikipedia).

Multiple comparisons problem
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Related pages

False coverage rate | False positive rate | Family-wise error rate | Testing hypotheses suggested by the data | Statistics | Analysis of variance | Statistical dispersion | Exploratory data analysis | Standard score | False discovery rate | ล idรกk correction | Coverage probability | Model selection | Poisson distribution | Interval estimation | Bonferroni correction | Qโ€“Q plot | Q-value (statistics) | Statistical inference | Data dredging | Duncan's new multiple range test | Sampling error | Statistical hypothesis testing | Closed testing procedure | Holmโ€“Bonferroni method | Boole's inequality | Test statistic | Look-elsewhere effect | Harmonic mean p-value