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A type I error rate of 5% (α = 0.05) was applied to each individual hypothesis test.
Hence, to select the best model, the savings for each individual hypothesis H can be expressed as (2) S H = S data - κ 1 S model - κ 2 S error where κ 1 = K 3 K 1 and κ 2 = K 2 K 1.
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Given the local ancestries of each individual, several hypothesis testing-based approaches have been proposed to test, one locus at a time, the null hypothesis that the AIM is unlinked to the complex-trait/disease for a dichotomous trait within a case-control study design.
Interestingly, in this way the significance level that results after the application of SGoF for each individual null hypothesis can be investigated.
The British Industrial Fatigue Board has given the individual hypothesis its scientific justification.
The local prediction for an individual hypothesis uses a kNN model based on the supporting examples.
Construct individual hypothesis predictions which will contribute to the overall call.
Rather, experience globally confirms the theory in which the individual hypothesis is embedded.
Empirical evidence does not bestow its confirmatory power on any one individual hypothesis.
Combine the hypotheses prediction into a final overall call by taking into account the individual hypothesis predictions and their respective confidence levels.
Local prediction based on individual hypotheses are combined into an overall call based on a reasoning method that can be adapted to the use case (screening, lead optimisation, risk assessment, etc).. 1. Construct individual hypothesis predictions which will contribute to the overall call.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com