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We use a one-sided binomial test to compute a P -value for this deviation.
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This study introduces a formal statistical test known as the "C test" to determine when there is a need to apply the beta-binomial test instead of the binomial test to screen a roadway network.
We use a binomial test to assess the statistical significance of the activity scores (see Methods).
We use a simple binomial test to evaluate the significance of the activity score defined here.
A log-binomial model was run to compute prevalence ratios and their significance level.
(***, ooo corresponds to p-values ≤ 0.001, where two-sided binomial tests are computed for each cluster. ooo Clusters contain fewer, *** clusters contain more DMPs than expected by chance. Pol II log2 FC: log2 fold change in Pol II binding averaged over all promoters per cluster).
One-tailed binomial tests were computed using custom Python code.
The binomial distribution was used to compute the significance level of the McNemar test.
A binomial probability based method to compute exact system reliability index is suggested.
A negative binomial model was used to compute the measured trough concentrations.
A negative binomial model was used to compute the KDIGO class at day 90.
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