Sentence examples for binomial test of the from inspiring English sources

This is the standard binomial test of the null hypothesis of no allelic balance H0: θ = 1/2 vs the alternative of allelic imbalance H1: θ≠1/2.

We did this using a binomial test of the number of samples with 'detection P-value' ≤0.05 (5% of the samples would be expected to have a P-value at this level by chance).

This is actually a significantly smaller bias than the 52.2% observed in the real data (P < 2 × 10−16 for a binomial test of the null hypothesis that the proportion in the real data is 50.7%).

(A) Distribution (mean, 50%CI and 95%CI as resulting from exact binomial tests) of the post-pandemic influenza seroprevalence by age group observed in the serological samples (grey; a sample is considered seropositive when HI titer is ≥ 40) and posterior distribution (mean, 50%CI and 95%CI) estimated with transmission models HR (blue), HSR (green) and HSWR (red).

For values falling outside this recommended range, a 95% confidence interval for the binomial test of proportions of the observed value is applied, and if the expected value of five percent falls within the confidence interval then the scale is deemed to be unidimensional.

p value: binomial test of whether the observed maternal:total ratio is greater than the expected 2 3 ratio.

p value, binomial test of whether the observed maternal:total ratio is less than the expected 2 3 ratio.

p value represents a binomial test of whether the observed maternal:total ratio is less than the expected 2 3 ratio.

In contrast to FET, the binomial test of GREAT assumes that the number of peaks in a locus and the locus length are proportional.

In contrast, the binomial test on the distribution of the infected cats among the 15 populations rejects the global binomial distribution hypothesis (p≈0.006).

We tested whether models were significantly better than random predictions using a one-tailed binomial test on the proportion of test sites falling outside the prediction resulting from a model that used 60% of the data for training and 40% for testing (Data S1) (Anderson et al. 2002).