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The most commonly used measure of variation is the standard deviation. It is a numerical value measuring how far data values are from their mean. The standard deviation value is small when the data are concentrated close to the mean, exhibiting slight variation or spread. The standard deviation value is never negative, it is either positive or zero. The standard deviation is larger when the data values are more spread out from the mean, which means the data values are exhibiting more variation.

Consider the waiting time for customers at the checkout at two supermarkets, X and Y. The average waiting time at both supermarkets is five minutes. At supermarket X, the standard deviation for the wait time is two minutes; at supermarket Y, the standard deviation for the waiting time is four minutes. As supermarket Y has a higher standard deviation, there is more variation in the wait time at supermarket Y. Overall, wait times at supermarket Y are more spread out or show more deviations from the average. In contrast, wait times at supermarket X are more concentrated near the average.

The lowercase letter s signifies the sample standard deviation, while the Greek letter σ (sigma, lowercase) represents the population standard deviation.

The sample standard deviation is given by the formula

Equation1

The population standard deviation is given by the following formula:

Equation2

This text is adapted from2.7 Measures of the Spread of the Data - Introductory Statistics | OpenStax

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Standard DeviationMeasure Of VariationData ValuesMeanNumerical ValueSpreadVariationWaiting TimeSupermarketsSample Standard DeviationPopulation Standard DeviationFormula

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4.3 : Standard Deviation

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4.1 : Was ist Variation?

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4.2 : Bereich

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4.4 : Standardfehler des Mittelwerts

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4.5 : Berechnung der Standardabweichung

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4.10 : Tschebyschews Theorem zur Interpretation der Standardabweichung

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