# How to graphically compare distributions of a variable for two groups with different sample sizes?

I'm not familiar with statistics terminology, so I can't google it unless I know what it's called.

My problem is this: I have a "test" (for lack of a better term) where I ask people to choose an answer. At the end of the test I'm asking if the person is a programmer or a designer, I assign a score from zero to ten and then I want to graph the results from both populations.

Problem is, right now I have more answers from developers (about 2 to 1). What is the fairest way of normalizing this data? The results are looking a lot like bell curves, should I just scale the graphs so that they match?

You can see the test here: http://method.ac/test

• You could generate density plots for the two groups. Quick-r has an example using the sm.density.compare function in the sm package.