Wow, I cannot believe what I am reading.
First off, taking the average of the overall USCF rating and subtracting the average blitz rating from it may be completely meaningless. Ok, you are trying to make a very simple linear best fit line (simple linear regression). Why did you choose linear regression over, say, polynomial regression? What about logistic regression (Ok, I can't remember if this actually applies here)? Some nonlinear regression? What is the correlation coefficient and what are the ranges of your confidence band (say, 95%) for the corresponding variables?
Seriously. Trying to apply a very basic model to what might actually need a more complex fit is a little silly. I'm curious as to how you came across to your conclusion (why linear regression over potentially better fitting regressions?), how many data points did you use (is the amount used significant???), and how confident are you in the best fit line that you chose?
I understand Adam continuously harps that "an average is good enough." However, the question has to be asked though: why is it good enough? Or is it simple the lazy approach?
I don't think a math degree has anything to do with the issue, nor the number of math or chess books you've read. Nor any chess title whatsoever.
I think you can compare, no doubt, but just as polling is a science, you have to be careful of the noise. If you could somehow take all the non-cheating chess.com players which have enough games played and do not have stale ratings, then you'd have what you want I think. I don't know how close it would be to comparing just the publicly-available averages. Myself, I usually hover in the low-2200s on chess.com blitz, which is within 25-50 points of my USCF rating.