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- perhaps mostly because it is most widely taught measure in undergraduate courses, and even in many graduate-level courses in statistics and inference
- it has an easily understood interpretation in terms of normal populations
- I suspect that many people find the mathematical operators involved in calculating it more familiar than those involved in calculing measures of spread based on L1 or other metrics
- statistical theory (and computer software) for ANOVA and other analogues of standard deviation has been much easier to create than that for L1 or other metrics
- there are classical results for the moments of distributions that do not involve absolute value or similar discontinuous functions

Q: Why is the standard deviation the most preferred measure of spread?

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Standard deviation is a measure of the spread of data.

Standard deviation is a measure of how spread out a set of numbers are from each other. It has a variety of uses in statistics.

The standard deviation is a measure of how spread out the numbers are. Three points is needed to calculate a statistically valid meaningful standard deviation.

They are measures of the spread of distributions about their mean.

The idea is to know how much the values "spread out" from the average.

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Standard deviation is a measure of the spread of data.

Because the standard deviation is a measure of the spread in scores. As individuals score more similarly, the spread gets smaller. Because the standard deviation is a measure of the spread in scores. As individuals score more similarly, the spread gets smaller. Because the standard deviation is a measure of the spread in scores. As individuals score more similarly, the spread gets smaller. Because the standard deviation is a measure of the spread in scores. As individuals score more similarly, the spread gets smaller.

The standard deviation is a measure of the spread of data.

It is a measure of the spread of the distribution. The greater the standard deviation the more variety there is in the observations.

Standard deviation is a measure of how spread out a set of numbers are from each other. It has a variety of uses in statistics.

The standard deviation is a measure of how spread out the numbers are. Three points is needed to calculate a statistically valid meaningful standard deviation.

They are measures of the spread of distributions about their mean.

The standard deviation of a set of data is a measure of the spread of the observations. It is the square root of the mean squared deviations from the mean of the data.

The idea is to know how much the values "spread out" from the average.

Standard deviation is a statistical measure. It may be used in psychology but is not restricted to that subject. It is a measure of the spread of the distribution of values of some attribute that is being measured.

standard deviation is the square roots of variance, a measure of spread or variability of data . it is given by (variance)^1/2

Yes. Standard deviation depends entirely upon the distribution; it is a measure of how spread out it is (ie how far from the mean "on average" the data is): the larger it is the more spread out it is, the smaller the less spread out. If every data point was the mean, the standard deviation would be zero!