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The main design focus is choosing the sample size that allows the clinical trial to discriminate between the null hypothesis of no difference and the alternative hypothesis of a specified difference of scientific interest.
The minimum sample size of 23 in each group achieves 91%% power to detect a difference of −5.0 between the null hypothesis that both group means are 5.0 and the alternative hypothesis that the mean of group 2 is 10.0 with estimated group standard deviations of 5.0 and 5.0, and with a significance level (alpha) of 0.05000 using a two-sided two-sample t test.
We next applied the rate test of Lande (1977) to distinguish between the null hypothesis of evolution by random genetic drift from the alternative hypothesis of natural selection.
Together with the set of optimal parameter values, HAPim returns the log-likelihood ratio test between the null hypothesis " a = d = 0" and its alternative.
A sample size of 107 achieves 80 % power to detect a difference of −2.2 between the null hypothesis of mean 49.5 and the alternative mean of 51.7.
Bootstrap techniques proved to be good at quantifying the difference between the null hypothesis and the variation observed in each situation, and to construct reliable tests and confidence intervals for each of the variation statistics analyzed.
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Cost difference between the null hypotheses cot and the total cost is the highest for Hypo1_A (Table 5) and Hypo1_B (Table 6), which signifies that the correlation between the fit values and experimental activities is not a random occurrence.
For comparing the quantitative variables between the groups, the null hypothesis that there was no difference between each group was tested using analysis of variance.
To test statistical heterogeneity across the study estimates, we estimated the variance corresponding to the between-study variability, and tested the null hypothesis that the between-study variability was absent.
The null distribution of b is computed by permuting data between conditions (assuming the null hypothesis of no effect of experimental condition) and refitting the above model.
The null distribution of b is computed by permuting data between conditions (assuming the null hypothesis of no effect of experimental condition or group membership) and refitting the above model.
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