Explanation:

Dispersion refers to the spread or variability of a set of data. Dispersion measures include Standard Deviation, Quartile Deviation, Mean Deviation, and Range. The quickest measure of dispersion to compute is the Range.

Range:
Range is the simplest measure of dispersion. It is the difference between the highest and the lowest value in a dataset. It is the quickest to calculate because it involves only two values and simple subtraction. It is often used as a quick measure of spread, especially when the dataset is small and the values are not too spread out.

Standard deviation:
Standard deviation is the most commonly used measure of dispersion. It measures how much the values in a dataset deviate from the mean. It is a more accurate measure of spread than the range, but it is also more complex to calculate. It involves squaring each value, finding the mean of those squared values, and then taking the square root of that mean. It is a useful measure of spread when the dataset is large and the values are spread out.

Quartile deviation:
Quartile deviation is a measure of the spread of a dataset based on the interquartile range. It is less sensitive to outliers than standard deviation. It is calculated by finding the difference between the first and third quartiles of the dataset. It is a useful measure of spread when the dataset is skewed or has outliers.

Mean deviation:
Mean deviation is the average of the absolute deviations of the values in a dataset from the mean. It is less commonly used than standard deviation and quartile deviation. It is calculated by finding the absolute value of the difference between each value and the mean, finding the mean of those absolute values, and then multiplying by a constant. It is a useful measure of spread when the dataset is small and the values are not too spread out.

Conclusion:
In conclusion, the quickest measure of dispersion to compute is the Range. It involves only two values and simple subtraction, making it easy to calculate. However, it is less accurate than standard deviation and quartile deviation, which are more commonly used when the dataset is large and the values are spread out.

Because it is too simply r=h-l.