# How Histograms Can Misrepresent Statistical Data

There are no hard and fast rules for how to create a histogram based on a set of statistical data; the person making the graph gets to choose the groupings on the *x*-axis as well as the scale and starting and ending points on the *y*-axis. Just because there is an element of choice, however, doesn’t mean every choice is appropriate; in fact, a histogram can be made to be misleading in many ways.

Although the number of groups you use for a histogram is up to the discretion of the person making the graph, there is such a thing as going overboard, either by having way too few bars, with everything lumped together, or by having way too many bars, where every little difference is magnified.

To decide how many bars a histogram should have, you should take a good look at the groupings used to form the bars on the *x*-axis and see if they make sense. For example, it doesn’t make sense to talk about exam scores in groups of 2 points; that’s too much detail — too many bars. On the other hand, it doesn’t make sense to group people’s ages by intervals of 20 years; that’s not descriptive enough.