Final answer:
The statement is true; the coefficient of variance is a more accurate measure of risk than standard deviation when comparing two pools of the same size as it normalizes the standard deviation by the mean, allowing for comparisons between datasets with different units or scales.
Step-by-step explanation:
The statement that the coefficient of variance is a more accurate measure of risk compared to standard deviation when comparing two different pools of exposure of the same size is True. The coefficient of variance is a standardized measure of the risk or dispersion of a set of values, and it is calculated as the ratio of the standard deviation to the mean. This normalization allows for comparison between data sets with different units or means because the coefficient of variance is unitless. In contrast, standard deviation alone does not account for the mean of the data sets, which can make direct comparisons between data sets misleading if they have vastly different means.
When comparing the variability of two sets of data, it's essential to consider the relative measure of variability, which is what the coefficient of variance represents. It is particularly useful when the sizes of the pools being compared are the same, ensuring a normalized comparison. This makes it a preferred measure over standard deviation for assessing relative risk.