Why shouldn't classes overlap when summarizing continuous data in a frequency or relative frequency distribution?

Classes in a frequency or relative frequency distribution shouldn't overlap to ensure that each data point is counted only once, maintaining the integrity of the distribution. Overlapping classes can lead to ambiguity in classification, skewing the results and misleading interpretations. Clear, non-overlapping classes provide a more accurate representation of the data's distribution, facilitating better analysis and comparison. This clarity is essential for effective data interpretation and decision-making.