X follows $N(0,\sigma_x^2)$ and Y follows $N(0,\sigma_y^2)$, and $X$ and $Y$ are independent. What is $P(X+Y>0 \mid X>0)$? If $\sigma_x^2=\sigma_y^2$ we can use symmetry and easily get answer 3/4, but what if $\sigma_x^2 \neq \sigma_y^2$?
2026-05-06 08:48:41.1778057321
What is $P(X+Y>0 \mid X>0)$ given that $X,Y$ two different normal?
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Let $X:=-\sigma_XN$ and $Y:=\sigma_YN'$, so $N,N'$ are independent $\mathcal N(0,1)$ variables. Let also $a:=\frac{\sigma_X}{\sigma_Y}>0$. Then $$X+Y>0\iff N'>aN.$$ Hence $$\Bbb P(X+Y>0\mid X>0)=\frac{\Bbb P(N'>aN,N<0)}{\Bbb P(N<0)}=1-2\,\Bbb P(N'<aN,N<0).\tag{$\star$}$$
Integrating out $N'$, we are thus reduced to studying the map $$f(a):=\Bbb P(N'<aN,N<0)=\mathbb E\!\left[\Phi(aN)\,\mathbf 1_{\left\{N<0\right\}}\right]\!,\qquad a>0,$$ where $\Phi$ is the c.d.f. of $\mathcal N(0,1)$, so $\Phi'(x)=\frac1{\sqrt{2\pi}}\,\mathrm e^{-\frac{x^2}2}$ for all $x\in\Bbb R$.
From 1. and 2., we deduce that $$f(a)=f(1)+\int_1^af'(t)\,\mathrm dt=f(1)-\frac1{2\pi}\Bigl[\arctan t\Bigr]_{t=1}^{t=a}=\frac14-\frac1{2\pi}\arctan a.$$
Recalling $(\star)$ and the value of $a$, we conclude that $$\mathbb P(X+Y>0\mid X>0)=\frac12+\frac1{\pi}\,\arctan\frac{\sigma_X}{\sigma_Y}.$$