![]() Probability of a type 1 error, a blue area the type 2 error, and a pair of green Test is shown, with the sampling distribution a dotted blue line, the populationĭistribution represented by a solid red line, a red shaded area delineating the In addition, a graphical representation of the T (the number of standard deviations from the null mean where an observationīecomes statistically significant), the number of degrees freedom, and the Result, along with, in descending order, the Noncentrality parameter δ, the Critical OnceĮntered, a press of ‘Calculate and transfer to main window’ inputsįrom there, a click of ‘Calculate’ in the main window produces the desired Respective standard deviations are known to us, as 15 and 17. We will set the mean of group 1 to 0 and the mean of group 2 to 10. Thus, 0 andġ0, 5 and 15, -2 and 8, etc., would all be acceptable. The specific numbersĮntered for the means of groups 1 and 2 are irrelevant, so long as theĭifference between them is the correct value, in our case 10. ‘Determine’ button calls up the appropriate window. Additionally,Įqual sized sample groups are assumed, meaning the allocation ratio of N1 to N2Īll that remains to be accounted for is the effect size. As significance level and power are given, we are free to To a t-test involving the difference between two independent means.Īs we are searching for sample size, an ‘A Priori’ power analysis isĪppropriate. Approaching Example 1, first we set G*Power In G*Power, it is fairly straightforward to perform power analysis forĬomparing means. What the means are as long as the difference is the same. This isīecause that she is only interested in the difference, and it does not matter Notice that in the first example, the dietician didn’t specify the mean forĮach group, instead she only specified the difference of the two means. Power this is the situation for Example 2.
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