Using the G* power website, download the free software and conduct a G* power analysis using the provided data.

There are 4 types of power analysis (a priori, post-hoc, criterion, and sensitivity). For the purposes of this class, we will focus on a priori power analysis since it is most commonly used when designing a research study (Hunt, n.d.).

Using the following parameters, complete a G* power analysis:

Alpha= .05

Power= .80

Expected Effect Size = In Week 2 Discussion 2, we practiced using the "Which Stats Test" Sage Tool.

Refer to the statistical test determined using that tool and select the large effect size for the appropriate test. (Note: if you aren't sure which test to use, you can use the t-test family, correlation). You will not lose points for choosing the incorrect test. The point here is to determine a test, input the parameters into G*power, and explain the results.

Figure 1 - Effect Size Benchmarks

Statistic	Small	Medium	Large
Means - Cohen's d	0.2	0.5	0.8
ANOVA - f	0.1	0.25	0.4
ANOVA - eta squared	0.01	0.06	0.14
Regression f-test	0.02	0.15	0.35
Correlation - r or point serial	0.1	0.3	0.5
Correlation - r squared	0.01	0.06	0.14
Association - 2 x 2 table - OR	1.5	3.5	9
Association - Chi-square - w or Phi	0.1	0.3	0.5

Source: Hunt. (n.d.). A researcher's guide to power analysis. Utah State University. Retrieved from https://research.usu.edu/irb/wp-content/uploads/sites/12/2015/08/A_Researchers_Guide_to_Power_Analysis_USU.pdf

G* Power Analysis

Variables: (Identify the variables used.)

[Enter your response here.]

Test Family and Statistical Test: (Identify the test family and statistical test used.)

[Enter your response here.]

G*Power Output:

[Copy and paste your G*Power output here.]

Output Parameters: (Explain each of the output parameters.)

[Enter your response here.]

References

[List references according to APA guidelines.]