Download G*Power and play around with it. See how changes in assumptions and parameters affect sample size estimates.

Submit:

1. a.Calculate the sample size needed given these factors:

◾one-tailed t-test with two independent groups of equal size

◾small effect size (see Piasta, S.B., & Justice, L.M., 2010)

◾alpha =.05

◾beta = .2

b.Assume that the result is a sample size beyond what you can obtain. Use the compromise function to compute alpha and beta for a sample half the size. Indicate the resulting alpha and beta. Present an argument that your study is worth doing with the smaller sample.

2. a.Calculate the sample size needed given these factors: ◾ANOVA (fixed effects, omnibus, one-way)

◾small effect size

◾alpha =.05

◾beta = .2

◾3 groups

b.Assume that the result is a sample size beyond what you can obtain. Use the compromise function to compute alpha and beta for a sample approximately half the size. Give your rationale for your selected beta/alpha ratio. Indicate the resulting alpha and beta. Give an argument that your study is worth doing with the smaller sample.

3.In a few sentences, describe two designs that can address your research question. The designs must involve two different statistical analyses. For each design, specify and justify each of the four factors and calculate the estimated sample size you’ll need. Give reasons for any parameters you need to specify for G*Power.

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