I'm trying to figure out if there's a difference across the main capitals in Europe and the voting preference of their inhabitants for extreme right political parties. So far I have categorized all people who voted into either extreme right (=1) or not (=0). That gives me a table with the capitals as rows, and one column that shows the number of people who voted for an extreme right party and one column for all people who did not. So far so good.
The next step would be to do a chi squared test to check if there is a significant difference in terms of distribution across the two groups (extreme right or not). The problem I have, is that the chi squared test is inappropriate for "large numbers". So I can sample my data by taking at random 5% of my data set and use that subset for my chi squared test, and repeat that 10 times to be sure that I'm getting the same outcome. But that seems not very elegant to me. The real question is now of course, how large does my data set have to be? And how much is too much data? I've Googled around a bit but I can't seem to get the right information. Any ideas?