Please let us know how is measure of dispersion useful in our result interpretation. Thank you.
Dispersion in statistics is a way of describing how spread out a set of data is. As the name suggests, the measure of dispersion shows the scattering or spreading of the data. It tells the variation existing within the data besides giving a clear idea about the distribution of the data. The measure of dispersion shows the homogeneity or the heterogeneity of the distribution of the observations. The measures of dispersion include:
- a) Range: Difference between two extreme observations of the data set.
- b) Quartile deviation: The quartiles divide a data set into quarters. The first quartile, (Q1) is the middle number between the smallest number and the median of the data. The second quartile, (Q2) is the median of the data set. The third quartile, (Q3) is the middle number between the median and the largest number. Quartile deviation or semi-inter-quartile deviation is Q = ½ × (Q3 – Q1).
- c) Mean deviation: Mean deviation is the arithmetic mean of the absolute deviations of the observations from a measure of central tendency.
- d) Standard deviation: The positive square root of the arithmetic mean of the squares of the deviations of the given values from their arithmetic mean.
Using these measures of dispersion, the results or observed data sets can be interpreted as how far the data spread out (left and right) of the mean.