Symmetric Distribution of Difference of Random Variables

probabilityprobability distributions

Assume that $ X$ and $Y $ are i.i.d continuously distributed random variables with the same probability density function, i.e $ f_X(x)=f_Y(y)$. If $Z=Y-X $, then $Z $ is symmetrically distributed around $ 0$.


I know I need to show that $f_Z(-z)=f_Z(z) $ for all $z\in
\mathbb{R} $
, but after writing the pdf of $ Z$ using convolution I'm struggling to see how that result would follow.

Best Answer

We have $$f_Z(z) = \int_{-\infty}^\infty f_X(x)f_Y(z+x) \, dx$$

By doing the substitution of $y=-z+x$ in the second equality below and using the property that $f_x(t)=f_y(t)$ (Note this is different from what you wrote, the argument is the same on both sides of the equality).

\begin{align} f_Z(-z) &= \int_{-\infty}^\infty f_X(x)f_Y(-z+x) \, dx\\ &=\int_{-\infty}^\infty f_X(y+z)f_Y(y) \, dy\\ &=\int_{-\infty}^\infty f_Y(y+z)f_X(y) \, dy\\ &=\int_{-\infty}^\infty f_Y(x+z)f_X(x) \, dx\\ &= f_Z(z) \end{align}

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