Please show graph and Download G*Power and then explore its content. See how changes in assumptions and parameters affect sample size estimates. (See Video Tutorial to Get Started.)

Submit a paper that details the following:

1. Calculate the sample size needed given these factors:
   • one-tailed t-test with two independent groups of equal size
   • small effect size (see Piasta & Justice, 2010)
   • alpha =.05
   • beta = .2
2. 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.
3. Calculate the sample size needed given these factors:
   • ANOVA (fixed effects, omnibus, one-way)
   • small effect size
   • alpha =.05
   • beta = .2
   • 3 groups
4. 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. Offer an argument to explain that your study is worth conducting with the smaller sample.
5. In a few sentences, describe two designs that can address your research question. For example, if you are examining the effectiveness of EFT for couples dealing with infidelity, you could use an ANOVA and compare EFT with Gottman's therapy and behavioral marital therapy; or you could conduct an RCT comparing EFT to a wait-list control group. 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.
6. Based on the video on Little "O" outcomes, describe some of the questions and ideas discussed in the video. What are some other little "O" outcomes that interest you and why?
7. Based on the MFT articles by Shadish and Brown, Piercy et al., and Gelin et al., describe the clinical significance and effect sizes of the treatment approaches addressed. How does effect size impact the clinical significance of these models? What can be said of the clinical significance of these models based on the effect sizes?