Sentence examples for binomial proportions based on from inspiring English sources
[15] Novel variants and/or duplication of the APP locus in sequenced patients were used to infer the probability of identical findings in the general population of sporadic CAA patients by computing exact confidence limits for binomial proportions based on available sample size [18].
†Exact binomial goodness-of-fit test for observed proportion of cases in listed area(s) to cases in untreated area compared with the expected proportion based on population size estimates.
All confidence intervals were calculated at the 99% level (alpha = 0.01) and those listed for proportions were based on binomial estimation of the standard error of a proportion.
The binomial test is based on the binomial distribution, while the Wilcoxon signed-rank test does not assume anything about the shape of the distribution.
Recently, Jonathon [4] gave a simple and interesting probabilistic proof of the above binomial identity, and he further extended this binomial identity based on the probabilistic method.
The two alternative null hypotheses: (i) equal binomial probability on each slope and (ii) binomial probability based on the slope total, were rejected (Table 1).
P value was calculated using a binomial statistic based on methodology described earlier [31,32].
Binomial testing based on U statistics and Fisher's exact test was used.
The 95% confidence interval (CI) for proportions is based on the exact binomial distribution.
Ninety-five perconfidencedence intervals (95% CI) for proportions were calculated based on binomial distributions.
