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The statistical power of both these tests for each alternative hypothesis was determined as well as that of the most powerful (or optimal) test (Bithell, 1995).
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The attractiveness of any hypothesis is determined in part by physical circumstances that have no logical connection to the diagnostic problem at hand.
The p-value of the CP-symmetry hypothesis is determined as the fraction of pseudoexperiments with χ2 larger than that measured in data.
It can be captured by the following decision matrix: On Savage's definition, the expected utility of accepting the hypothesis is determined by the probability of the hypothesis, together with the utilities of each of the four outcomes.
A GUHA hypothesis is determined by the ordered pair of cedents (antecedent (A) and succedent (S)) and by a quantifier.
In general, the statistical hypothesis is determined by considering the balance between the risks and benefits of the standard arm and the test arm.
Statistical support for alternative hypotheses was determined by constructing a constraint trees for each alternate hypothesis and using the constraints to filter trees from each analysis (100 bootstrap trees from maximum-likelihood, 1000 trees from neighbor-joining analysis, and 320,000 trees from Bayes) in Paup* [120].
Relative support for alternative hypotheses was determined using Akaike Information Criterion AICC) and Akaike weights [ 40, 41].
As this was a pilot study, no a priori hypotheses were determined based on clinical or psychological outcomes.
To test this hypothesis, poxvirus was determined in samples of healthy skin, skin lesions and blood from the two beluga whales.
The significance of finding a fraction of concordant observations that differed from the null hypothesis expectation value was determined using the cumulative binomial distribution.
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