Sentence examples for binomial test revealed that from inspiring English sources

A binomial test revealed that the proportion of symmetric images being chosen as most sexually dimorphic significantly differed from chance (chosen = 6/6, chance 3/6, p = .031).031

A binomial test revealed that participants responding incorrectly on 4 or more of the catch trials were not performing significantly above chance.

A binomial test revealed that patients with emerging symptoms were significantly more often under the age of 18 years (9 patients under the age of 18 vs. 2 patients above the age of 18: one-tail p = 0.033).

Taking as our null hypothesis that, in the event of no consistent retinotopic mapping, the correlation coefficients should be equally likely to be positive or negative for a given quadrant, a binomial test revealed that for our data this null hypothesis could be rejected (P= 0.007; exact binomial test, two-tailed).

Three follow-up exact binomial tests revealed that those with psychiatric diagnosis and no antidepressant medication were more likely to have below median placental methylation at LEPR/cg21655790 (FDR adjusted p = 0.01).

Binomial tests revealed that rates of adaptive switching among 7- and 9-year-olds who experienced regret were highly unlikely to be due to chance (in both cases, p <  .001).001

Similarly, only 27% of the 15 Sham3 rats swam to the correct corner first during the initial Test Probe (not different from chance, p >.1), but during Retest, 60% of 15 Sham3 rats swam to the correct corner first, and binomial tests revealed that their performance was significantly above chance (p =.004, one-tailed).

GO-enrichment analysis of the genes that are differentially expressed using the binomial test revealed largely expected results, e.g., alpha factor−stimulated cells had as their top five categories "conjugation," "conjugation with cellular fusion," "sexual reproduction," "interaction between organisms," and "response to pheromone".

A binomial test revealed a positive relationship between antibiotic consumption and resistance (p < .001) but multiple regression modelling did not produce any significant predictors of study outcome.

As the overdispersion parameter α was significantly different from zero and the Vuong likelihood ratio test revealed that the zero-inflated model was preferred against the standard negative binomial model, a Zero-Inflated Negative Binomial (ZINB) model was chosen, as it accounted both for the excess zeros and for the extra heterogeneity in the outcome [ 21, 22].

Diagnostic tests revealed that a negative binomial regression model was more appropriate than a regular Poisson model or zero-inflated negative binomial modelg.