Consider a relative frequency distribution table of the number of clocks sold at different price ranges represented as class intervals and class boundaries. This table represents the relative proportions of each quantitative value in the data set.

Such relative frequency tables are visualized using a graph called relative frequency histograms. Here, the vertical axis represents the relative frequencies of each class, and the horizontal axis represents the class boundaries or the class midpoints. 

Then, the vertical bars of equal width are drawn without gaps, connecting the class boundaries with the relative frequency values. From such histograms, one can understand how often any value occurs relative to the others in the data set.

Suppose the data are expressed in percentage frequencies; they are then visualized using the percentage frequency histogram. Here, the second bin shows that 17 percent of the total clocks sold fall between the price of 10.5 and 16.5 dollars. 

If the data set is too large, plotting them on a histogram makes it easier to interpret.