when comparing two distributions, it would be best to use relative frequency histograms rather than frequency histograms when

When comparing two distributions, it is best to use relative frequency histograms rather than frequency histograms when the distributions have different numbers of observations. Relative frequency histograms allow us to compare the proportion of observations in each class relative to the total number of observations, making the comparison meaningful regardless of different sample sizes. Frequency histograms show the raw counts, which can be misleading when sample sizes differ. Other situations where relative frequency histograms are useful include when the distributions have different shapes, spreads, centers, or when there are outliers. But the key case is when the numbers of observations differ between the two distributions. In summary: Use relative frequency histograms when comparing distributions with different total sample sizes for clearer and fairer comparisons.