Section 1: Reporting thetTest Results

Using bpstudy.sav, conduct an independent samplesttest in SPSS with gender as the grouping variable (male = 1; female = 2) and HR1 (heart rate) as the outcome variable.

Paste the SPSS output and then report:

• The sample size for males (n1) and sample size for females (n2).
• The means for males (M1) and females (M2) on HR1.
• The calculated mean difference (M1 -M2).
• The standard deviations for males (s1) and females (s2) on HR1.
• The Levene test (homogeneity of variance assumption) and interpretation.
• t,degrees of freedom,tvalue, and probability value. State whether or not to reject the null hypothesis. Interpret the results.
• Calculate Cohen'sdeffect size from the SPSS output and interpret it. Specifically, if the homogeneity of variance assumption is met, divide the mean difference (M1 -M2) by eithers1 ors2. Violation of the homogeneity of variance assumption requires calculation ofSpooled. Homogeneity assumed:
• Cohen'sd= (M1 -M2) s1 or Cohen'sd= (M1 -M2) s2
• To be comprehensive, report Cohen'sdbased on a calculation withs1 and a calculation withs2. Round the effect size to two decimal places. Interpret Cohen'sdwith Table 5.2 of your Warner text.

Section 2: Post-hoc Power Analysis

Open G*Power. Select the following options:

• Test family =ttests.
• Statistical test = Means: Difference between two independent groups (two groups).
• Type of power analysis = Post hoc: Compute achieved power.
• Tails(s) = Two.
• Effect sized= Cohen'sdobtained from Section 1 above (using eithers1 ors2).
• err prob = standard alpha level.
• Sample size group 1 =n1 from Section 1 above.
• Sample size group 2 =n2 from Section 1 above.
• ClickCalculate.

Provide a screen shot of your G*Power output. Report the observed power of this post-hoc power analysis. Interpret the level of power in terms of rejecting a null hypothesis. Do you have sufficient power to reject a false null hypothesis? Interpret power in terms of committing a Type II error.

Section 3: A Priori Power Analysis

In G*Power, now select:

• Type of power analysis = A priori: Compute required sample size.
• Input effect sizedfrom Section 1.
• Specify err prob.
• Specify Power (1 - ) = .80.
• Set the Allocation ratio to 1 (i.e., equal sample sizes).
• Press Calculate.

Provide a screen shot of your G*Power output. Interpret the meaning of a .80 power value. Specifically, report the estimatedn1,n2, and totalNto achieve obtain a power of .80. How many total subjects (N) would be needed to obtain a power of .80? Would you have expected a requiredNof this size? Why or why not?

Next, in G*Power, change the Cohen'sdeffect size value obtained in Section 1 and set it to .50 (conventional "medium" effect size). ClickCalculate. How many total subjects (N)are needed to obtain a power of .80? Compare and contrast these two estimatedNs.

In conclusion, reflect on the importance of conducting an a priori power analysis in psychological research plans.