Recall that the measures of center, variation, distribution, outliers, and changing data characteristics over time are essential for effective data analysis. Of these, the measures of variation describe the dispersion or spread of the values in a dataset. Consider the datasets on heights of randomly selected school children and that of students of a particular grade. Although the plots of the two datasets have the same mean, they vary significantly in how data points are dispersed or positioned. The plot on the left has the values more spread out than the one on the right. Therefore, instead of the mean, variation is used to measure the spread of values in the datasets. Range, standard deviation, and variance are commonly used measures of variation. The range is the difference between the maximum and minimum data values. The standard deviation measures how much the data value varies about the mean, while the variance is the square of the standard deviation. Thus, each measure of variation helps to uniquely analyze and interpret the differences between datasets.