Please excuse me if this has been asked before, I searched and couldn't find what I was looking for. The basic setup of my question is this - I have data on all of the students for a school. I then conduct two different surveys (for example, a paper-based survey and an internet-based survey), that try to target all of the students. This results in 2 groups of respondents. So far, I have done chi-squared test of goodness of fit on various demographic features (e.g. age bracket distribution) as well as measured effect size, comparing each survey respondent group with the overall student population. For example:
chi squared and p-value for survey 1 and population: 1057.11668626 3.95209518794e-225
Cramer's v: 0.219299550203
chi squared and p-value for survey 2 and population: 20750.6706798 0.0
Cramer's v: 0.971610827539
I want to say that one group of respondents is more representative of the general student population than another. Based on the above results, for example, I'd say that the distribution in age for the respondents of survey 1 is more similar to the overall student population, than "" of survey 2.
Is there a more proper/better way to compare how representative various sample groups are with a population?