Sentence examples for inflated probability from inspiring English sources

The inflated probability of false-positive results here is therefore due to other factors, such as our larger sequence length and larger effective population size.

In a situation with no predefined hypothesis, P-value adjustment for multiple testing may be made to counteract the inflated probability of a type I error.

This poses problems of interpretation when an association is found, because adjustment has to be made to p-values to take into account the inflated probability of chance findings.

The problem is that since you're under pressure from the journal editor to tell your story leading up to your conclusion without talking about all the blind alleys and accidents, it actually distorts the story itself because it inflates the probability that what you discovered is really significant.

Although methods exist to adjust total variance by removing an estimated proportion of within-individual variation [14], such methods may inflate the probability of obtaining a false positive result (i.e., increased Type I error).

For large s, the look-ahead effect can inflate the probability of fixation of allele 2 by several orders of magnitude.

This inflates the probability of a false discovery above the nominal P value, and tests of marginal significance should be interpreted cautiously given the number of hypotheses tested.

Judgment overconfidence is a particularly important bias [ 4] in healthcare as overconfident clinicians (erroneously inflating the probability of being correct) are less likely to seek information that could increase the chances of a correct clinical judgment [ 5].

Whereas the average of 62% males in ADHD samples may be methodologically sound (as it reflects the conservative reports of 2 1 male:female ratio in ADHD), a higher proportion of males than females in OCD samples may artificially inflate the probability of finding cases of ADHD.

Specifically, for cases where mean square statistics fell within the range 0.7 – 1.3, the t-statistics increased in magnitude as sample size increased, therefore for the t-statistic the Type I error rate was inflated and the probability of identifying misfit where none was identified by the mean square statistics increased with sample size.

Naïve Bayesian models assume independence between all input datasets, which can artificially inflate predicted probabilities when this assumption is violated (e.g. when multiple very similar datasets are integrated).