Relative dispersion = coefficient of variation = (9000/45000)(100) = 20.
Central tendency is measured by using the mean, median and mode of a set of numbers. Variation is measured by using the range, variance and standard deviation of a set of numbers.
Sets of data have many characteristics. The central location (mean, median) is one measure. But you can have different data sets with the same mean. So a measure of dispersion is used to determine whether there is a little or a lot of variability within the set. Sometimes it is necessary to look at higher order measures like the skewness, kurtosis.
No. The average of the deviations, or mean deviation, will always be zero. The standard deviation is the average squared deviation which is usually non-zero.
Standard deviation is a measure of variation from the mean of a data set. 1 standard deviation from the mean (which is usually + and - from mean) contains 68% of the data.
The Absolute Measure of dispersion is basically the measure of variation from the mean such as standard deviation. On the other hand the relative measure of dispersion is basically the position of a certain variable with reference to or as compared with the other variables. Such as the percentiles or the z-score.
The units of dispersion are dependent on the units of the data being measured. Common measures of dispersion include variance and standard deviation, which have square units and the same units as the data being measured, respectively. Another measure, such as the coefficient of variation, is a unitless measure of dispersion relative to the mean.
Relative dispersion = coefficient of variation = (9000/45000)(100) = 20.
These measures are calculated for the comparison of dispersion in two or more than two sets of observations. These measures are free of the units in which the original data is measured. If the original data is in dollar or kilometers, we do not use these units with relative measure of dispersion. These measures are a sort of ratio and are called coefficients. Each absolute measure of dispersion can be converted into its relative measure. Thus the relative measures of dispersion are:Coefficient of Range or Coefficient of Dispersion.Coefficient of Quartile Deviation or Quartile Coefficient of Dispersion.Coefficient of Mean Deviation or Mean Deviation of Dispersion.Coefficient of Standard Deviation or Standard Coefficient of Dispersion.Coefficient of Variation (a special case of Standard Coefficient of Dispersion)
Absolute dispersion usually refers to the standard deviation, a measure of variation from the mean, the units of st. dev. are the same as for the data. Relative dispersion, sometimes called the coefficient of variation, is the result of dividing the st. dev. by the mean, hence it is dimensionless (it may also be presented as a percentage). So a low value of relative dispersion usually implies that the st. dev. is small in comparison to the magnitude of the mean, as in a st. dev. of 6cm for a mean of 4m would give a figure of 0.015 (1.5%) whereas with a mean of 40cm it would be 0.15 or 15%. However with measurements either side of zero and a mean close to zero the relative dispersion could be greater than 1. As is usual, interpret with caution.
The coefficient of variation is calculated by dividing the standard deviation of a dataset by the mean of the same dataset, and then multiplying the result by 100 to express it as a percentage. It is a measure of relative variability and is used to compare the dispersion of data sets with different units or scales.
The coefficient of variation (CV) is a measure of relative variability, indicating the degree of dispersion of a distribution relative to its mean. A high CV value suggests greater variability, while a low CV value suggests more consistency. It is useful for comparing the variability of different datasets with differing units of measurement.
No. A range is one measure of variation. It is easy to find, but it is also a rather crude measure.
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Having only the mean is not sufficient to identify outliers. You need some measure of dispersion.
The variance or standard deviation.
It is a measure of the spread or dispersion of the data.