A.H. comments on The Geometric Expectation

[A.H.]

The infinite non-uniform discrete case is not much more difficult. If $X$ is a finite or countably infinite set, $f:X\to R^{\ge 0}$ assigns a nonnegative value to each $x\in X$, and $P$ is a probability distribution on $Y$, then $E_{x\sim P}f\left(x\right)={\sum }_{x\in X}P\left(x\right)f\left(x\right)$

Very minor, but shouldn’t this read ”$P$ is a probability distribution on $X$” not $Y$?