Disadvantage of Range

C

The range uses only the highest and the lowest observations and ignores all the observations in the middle. This may not be indicative of the dispersion if the two extreme observations are outliers.

The correct answer is A. It is not in the same units as the original data.

The range is a measure of dispersion that indicates the spread or variability of a dataset. It is calculated by subtracting the minimum value from the maximum value of the data. While the range provides a simple and straightforward way to assess dispersion, it does have a significant disadvantage.

The disadvantage of the range is that it is not in the same units as the original data. This means that the range does not account for the scale of measurement used in the dataset. For example, if you are measuring the heights of individuals in centimeters, the range will be in centimeters as well. However, if you decide to measure the heights in inches instead, the range will be in inches. As a result, the range cannot be used to make meaningful comparisons between datasets that have different units of measurement or scales.

To illustrate this further, consider two datasets: one measures weights in kilograms, and the other measures ages in years. If we calculate the range for each dataset separately, we will end up with different numerical values, which cannot be directly compared. This lack of standardization makes it difficult to interpret and compare the dispersion across different datasets accurately.

To overcome this disadvantage, statisticians often use other measures of dispersion, such as the standard deviation or the coefficient of variation, which normalize the dispersion relative to the mean and allow for meaningful comparisons between datasets with different units of measurement. These alternative measures take into account the scale of measurement and provide more robust insights into the spread of the data.