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A lot is lost here by using notation that looks like it is rigorous math, but is actually pretty vague. For example, are X and Y indicators for the same flip? If so, they are mutually exclusive, X=Y is contradictory, and hence P(X=Y)=0. If they are samples from different flips (and your coin is the usual idealized one) then X and Y are independent random variables and P(X=Y)=0.25. It's just like if X~N(0,1), Y~N(0,1) and you want to know the distribution of X-Y. You need to know what the PDF of (X,Y) looks like. Well, you don't know. X and Y could be correlated or they might not be. e.g. if could be that (X,Y)~N( (0,0), [(1,0),(0,1)] ) or maybe (X,Y)~N( (0,0), [(1,1/2),(1/2,1)] ). The distribution of X-Y cares how correlated X and Y are. |
Isn’t it 0.5?