Summary statistics for contingency tables | Multiple comparisons | Statistical hypothesis testing
In statistics, the false discovery rate (FDR) is a method of conceptualizing the rate of type I errors in null hypothesis testing when conducting multiple comparisons. FDR-controlling procedures are designed to control the FDR, which is the expected proportion of "discoveries" (rejected null hypotheses) that are false (incorrect rejections of the null). Equivalently, the FDR is the expected ratio of the number of false positive classifications (false discoveries) to the total number of positive classifications (rejections of the null). The total number of rejections of the null include both the number of false positives (FP) and true positives (TP). Simply put, FDR = FP / (FP + TP). FDR-controlling procedures provide less stringent control of Type I errors compared to family-wise error rate (FWER) controlling procedures (such as the Bonferroni correction), which control the probability of at least one Type I error. Thus, FDR-controlling procedures have greater power, at the cost of increased numbers of Type I errors. (Wikipedia).
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Please Subscribe here, thank you!!! https://goo.gl/JQ8Nys The Probability of a False Positive in a Drug Test
From playlist Statistics
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Please Subscribe here, thank you!!! https://goo.gl/JQ8Nys Hypothesis Test for a Population Percentage using the P-Value Method and StatCrunch
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