Answer:
B. relative frequencies.
Explanation:
Relative frequencies are the proportion of observations in a particular category out of the total number of observations. They are calculated by dividing the frequency of a particular category by the total frequency.
For example, if there are 100 observations in a dataset and 20 of them are in the "male" category, then the relative frequency of the "male" category is 0.2, or 20%.
Relative frequencies are used to compare proportions when the totals are unequal. This is because the absolute frequencies, or the number of observations in each category, can be misleading if the totals are different. For example, if there are 100 observations in one category and 10 observations in another category, then the absolute frequency of the first category is 10 times greater than the absolute frequency of the second category. However, if we calculate the relative frequencies, we see that the two categories actually have the same proportion of observations or 10%.
Therefore, relative frequencies are a more accurate way to compare proportions when the totals are unequal.