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I have a sample of 200 independent networks and I want to test the hypothesis that majority of vertices belong to one giant component. I wonder what is the appropriate approach to do that.
I crawled the Google Scholar, but I didn’t find any pointers about my problem. Could I use standard chi-square goodness-of-fit test, where the first set of frequencies counts size of giant component (i.e., number of vertices in a giant component) and the second set counts the size of the rest components (i.e., total number of vertices in a sample – number of vertices in a giant component)?
Any suggestions would be greatly appreciated.
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