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the real-world situation or problem you selected to address, the independent and dependent variables you would study and the number of levels of the independent variable, the statistical null and alternative hypotheses, a description of what information the effect size would tell you that the probability value would not tell you, explain what additional information confidence intervals around means (or around mean differences) would give your reader; explain when would you need to report a post hoc test and why; and using realistic numbers for values of degrees of freedom, sample size, F-ratio, confidence interval (s) (if appropriate), and post hoc results (if appropriate), report hypothetical results in a few sentences using correct APA format

Below is what I have done so far and was told itg was incorrect I need to add another sample can you assist me.

There are three Chevrolet dealers in Jamestown, New York. The mean weekly sales at Sharkey Chevy and Dave White Chevrolet Dave John Chevrolet are about the same. However, Tom Sharkey, the owner of Sharkey Chevy, believes his sales are more consistent. Below is the number of new cars sold at Sharkey in the last seven months and for the last eight months at Dave White. Do we agree with Mr. Sharkey? Use the .01 significance level.
(1) Independent variable: Number of groups and Dependent variable: Number of sales
(2) Here, the three samples are independent; that is, the sales in one shop do not affect the sales in the others. Therefore, a t- test for independent samples is appropriate.
(3) H0: Sales at Sharkey are about the same as at Dave White, and Dave John that is, �2  �1
Ha: Sales at Sharkey are more consistent, that is, �2 > �1
Upper-tailed t- test for the difference in means of independent samples with α = 0.01
df = n1 + n2 – 2 = 7 + 8 – 2 = 13 and the critical value of t for α= 0.01 is 2.65
Decision Rule: If t- score > 2.65 reject H0 and accept Ha

Sharkey Dave White & Dave John
98 75 66
78 81 82
54 81 70
57 30 58
68 82 48
64 46 77
70 58 60


Means 69.85714286 69.25
SDs 14.79221159 22.95181288

n1 = 7, n2 = 8, x1-bar = 69.857, x2-bar = 69.25, s1 = 14.792, s2 = 22.952
Pooled estimate of SD = S = Ö[{(n1 – 1)s1^2 + (n2 – 1)s2^2}/(n1 + n2 – 2)}]
S = Ö[{(7 – 1) * 14.792^2 + (8 – 1) * 22.952^2}/(7 + 8 – 2)}] = 19.612
SE = S * Ö {(n1 + n2)/(n1n2)} = 19.612 * Ö{(7 + 8)/(7 * 8)} = 10.15
t = [(x1-bar – x2-bar) – (µ1 – µ2)]/SE = (69.857 – 69.25)/10.15 = 0.06
Since 0.06 < 2.65, we fail to reject H0
Conclusion: There is no statistical support to Mr. Sharkey's belief. At α = 0.01, it cannot be concluded that his sales are more consistent.
Describe what information the effect size would tell you that the probability value would not tell you.
(4) In this example, effect size is the amount of sales that Mr. Sharkey believes his shop exceeds. This hypothetical value tells of the amount of sales to expect from the results of the calculations, whereas the p- value tells the probability of this actually happening.