Normalizing Interconnected Data: A-A, A-B, B-B

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SUMMARY

The discussion focuses on normalizing interconnected data between two distinct sets of items, A and B, to analyze the differences in connection types: A-A, A-B, and B-B. The user proposes a normalization formula for A-A connections as the number of connections divided by the product of A's total items (A*A) and similarly for A-B connections (number of connections/(A*B)). Additionally, the suggestion to apply a chi-squared goodness of fit test is made to evaluate whether the connection distributions between A-A and A-B are statistically significant.

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Spiderman
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This may be a simple problem, but I wanted to run it by some other people before using my solution.

I have two distinct sets of items A and B which may or may not be connected to one another. I want to know whether or not the interconnections between them are significiantly different, i.e are the number of connections between A-A, A-B, and B-B different - are A's connected more to A's, for example. However, there are many more B's than A's. Normally I would just divide the value by the number of items, but how do I do this with interconnected items? Is the normalized value of the number of A-A connections =

number of connections/(A*A)

And similarly for A-B: number of connections/(A*B)

I can't determine if this is right or not.
 
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you may want to do a chi squared goodness of fit test. seeing if a-a matches the data for a-b..ect
 

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