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There are other alternatives, of course. The [[median]] and [[mode]] are both measures of [[central tendency]]. To describe the [[statistical dispersion]], we can use the [[statistical range]], the [[interquartile range]], or the [[absolute deviation]]. |
There are other alternatives, of course. The [[median]] and [[mode]] are both measures of [[central tendency]]. To describe the [[statistical dispersion]], we can use the [[statistical range]], the [[interquartile range]], or the [[absolute deviation]]. |
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See also [[skewness]] and [[kurtosis]]. The [[Gini coefficent]] was originally developed to measure income inequality, but can be used for other purposes as well. |
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Revision as of 02:26, 23 September 2001
The easiest way to approach this subject is to focus on what we have and what we want to achieve:
- We have a set of observations which we want to summarize.
- We want to communicate as much as possible as simply as possible.
Statisticians commonly try to describe the observations in
- a measure of central tendency like the arithmetic mean, and
- a measure of statistical dispersion like the standard deviation.
There are other alternatives, of course. The median and mode are both measures of central tendency. To describe the statistical dispersion, we can use the statistical range, the interquartile range, or the absolute deviation.
See also skewness and kurtosis. The Gini coefficent was originally developed to measure income inequality, but can be used for other purposes as well.
back to statistical theory -- summarizing statistical data