Sentence examples for false significance from inspiring English sources

How irresistible it is to find false significance in chance occurrences.

False significance has been handled with Bonferroni correction.

We accounted for the potential for this pseudo-replication to generate false significance (type I error) in two ways.

This question arises because of the increased risk of Type I errors (findings of false "significance") when multiple simultaneous hypotheses are tested at set p-values.

The large number of tests performed on this rather small sample also increases the risk of finding false significance and this should be taken into consideration.

To empirically demonstrate that variance inflation results in the false significance of gene sets, we randomly permuted the sample labels associated with each of the 202 Gene Expression Omnibus data sets 10,000 times, and then performed a gene set analysis on each permutation using a common independence assumption method.

To control for possible Type I errors, the upper limit of number of false significances was calculated by the following formula: (number of tests - number of significant tests on the level of α) × α/ 1-α).

As the secondary outcomes involve a great number of statistical analyses, there is risk of false significances.

When F ST was set to zero, the proportion of false significances was 1%, which is lower to the intended value of 5%.

Analyses of correlations between IGF-1, pain, and CSF markers (Table 4) comprised a total of 18 analyses, and the upper level of the number of false significances was 0.79, which means that one of the significances might be false.

To control possible Type I errors, the upper limit of expected number of false significances for the analyses was calculated by the following formula: α/1– α × (number of tests – number of significant tests), where α is the significance level.