We have $X_1,X_2,X_3 \sim \operatorname{Uniform}(0,1)$ and we want to find the probability that the largest realized value among them is greater than the sum of the other two. I know that we can make a symmetry argument, define limits, and integrate, but I want to know if there is a way to do it using order statistics so that $$ 3P(X_1>X_2+X_3)=P(X_{(1)}+X_{(2)}< X_{(3)}) =P(X_{(1)}< X_{(3)}-X_{(2)}) $$ I tried starting from $$P(X_{(1)}<X_{(3)}-X_{(2)})=F_{X_{(1)}}(x_{(3)}-x_{(2)})=\sum_{i=1}^{3}\binom{3}{i}F(x_{(3)}-x_{(2)})^i[1-F(x_{(3)}-x_{(2)})]^{3-i}$$ I haven't worked through all the algebra of the resulting expression, but it looks to me like I'm going to get something that is in terms of the difference $x_{(3)}-x_{(2)}$ which is good generally, but doesn't give me the straight numerical answer I'm looking for (which I know through direct calculation is 1/2).
Is my above approach using order statistics valid and, if so, why isn't it giving me the answer I want? Thanks!
I don't understand your equality
$$P(X_{(1)}<X_{(3)}-X_{(2)})=F_{X_{(1)}}(x_{(3)}-x_{(2)})$$
You seem to be plugging the CDF , but that does make much sense to me.
If (say) you have two rv $X,Y$ and you want to calculate $P(X\le Y)$, you can't just write $P(X\le Y) = F_X(y)$ because $y$ means nothing. And you can neither write $P_X(Y)$ because that would be a random variable (and the probability should be a number). What you can write is $P(X\le Y \mid Y=y)=F_X(y)$, but that would hardly lead you anywhere, I think.