Vol. 5, No. 9
from Professor Cleary
of variation is a measure of how much variation exists in relation to
the mean, so it represents a highly useful—and easy—concept in data analysis.
But Dr. Barbara SeVille's guess was a meaningless collection of jargon
that she had picked up from a variety of sources. By obfuscating this
simple technique, she was in fact robbing her trainees of the opportunity
to gain another tool for data analysis.
The standard deviation alone is sometimes not particularly useful, without a context within which one can determine meaning. For example, knowing that the standard deviation is 1.76 has no meaning; but understanding that a standard deviation of 20 had been anticipated gives a context that recognizes that variability is less than expected. Knowing that the standard deviation has historically been .5 or less for a particular dimension, on the other hand, 1.76 would be considered high. Without perspective, the figure for standard deviation has limited meaning.
The coefficient of variation provides a reference, by looking at the ratio of a standard deviation to a mean.
If the number is large, the data has a great deal of variability with respect to the mean.
If the number is smaller, this reflects a small amount of variability relative to the mean.
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