I'm analyzing a number of various processes, trying to find the one that
consistently results in the highest outcome. Below is a subset of results.
Case Mean StDev SEMean Q1 Median Q3 SSQ SkewnessKurtosis CV
1 5.07 3.63 0.39 2.61 5.06 6.92 3411 0.43 0.33 0.72
2 5.02 3.66 0.52 3.17 4.63 6.60 1876 1.02 3.29 0.73
3 4.14 3.14 0.50 1.98 4.69 5.28 1042 0.37 1.39 0.76
4 3.50 2.66 0.48 1.86 3.02 5.33 591 0.67 0.68 0.76
5 3.70 2.89 0.32 1.18 3.60 5.96 1778 0.04 -0.69 0.78
6 3.49 2.78 0.43 1.16 3.40 5.66 829 -0.62 0.65 0.80
7 3.76 3.00 0.55 1.20 3.85 5.85 683 0.24 -0.64 0.80
8 4.91 3.95 0.37 2.57 4.43 6.59 4591 1.22 2.28 0.80
9 7.67 6.17 0.94 2.45 8.23 11.84 4126 -0.02 -0.68 0.80
10 4.11 3.39 0.24 1.89 4.31 5.92 5457 0.13 2.54 0.82
11 4.11 3.40 0.44 2.25 4.21 6.26 1695 0.08 0.40 0.83
12 6.28 5.32 0.89 1.86 6.20 10.55 2410 0.38 -0.02 0.85
13 3.76 3.19 0.36 1.41 4.22 5.79 1910 -0.03 -0.40 0.85
14 3.35 2.85 0.27 1.42 3.42 5.30 2215 -0.01 0.27 0.85
15 7.50 6.42 0.90 3.42 7.68 12.57 4925 -0.44 0.37 0.86
16 3.85 3.34 0.38 1.10 4.36 5.53 1965 0.12 0.12 0.87
17 6.14 5.38 0.98 2.47 4.76 7.25 1972 1.24 1.19 0.88
18 6.90 6.05 0.67 1.37 6.08 11.28 6871 0.64 -0.46 0.88
19 7.11 6.25 0.81 2.24 7.58 11.23 5340 0.06 -0.49 0.88
20 5.75 5.06 0.96 1.12 5.61 8.63 1615 0.99 1.90 0.88
My tentative hunch is to use the last column --- Coefficient of Variation
--- as the over-riding criterion. Thus case number 1 is the best.
The first-impression-approach of simply using the highest Mean, case number
9, would appear to be a grave mistake, as the dispersion of outcome is so
great.
Please comment on the above thinking. Do you agree? Or am I disregarding
something important?
Thank you for your time and attention.
Nicholas
Salt Lake City, Utah
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