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

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  1. 13 July, 05:54
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    When comparing two distributions, it would be best to use relative frequency histograms rather than frequency histograms when the distributions have different sample sizes.

    Step-by-step explanation:

    The sample size of a distribution is the number of observations that constitute it. When two data sets need to be compared, and the sample size is different, a Relative Frequency Histogram would be the best way to compare them since they present a probability distribution in a graphical form. This means that histogram heights can be understood as probabilities (results to occur within a given population)

    For example, if distribution A has a sample size of n (A) = 23 and distribution B has a sample size of n (B) = 23000, a Frequency Histogram would display results a thousand times greater for data set B, but, a Relative Frequency Histogram would instead show the results drawn on the same scale. So, the best way to compare two distributions with different sample sizes is by using a Relative Frequency Histogram.
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