Given that $T_1, T_2$ are iid $\text{exp}(\lambda)$ variates.
I want to find the cdf $F_T(t)$ where $T=T_1-T_2$
My Attempt
$F_T(t) =_1 P(T<t) = P(T_1-T_2<t) = P(T_1<T_2 + t)$
Where $=_1$ is true according to the definition of CDF.
But I'm stuck here, how can I continue from this step?
If $T_{1}$ and $T_{2}$ are independent then
If $t\geq 0$,
$$P(T\leq t)=P(T_{1}-T_{2}\leq t)=\mathbb{E}(\mathbf{1}_{\{T_{1}-T_{2}\leq t\}})\\=\mathbb{E}(\mathbb{E}(\mathbf{1}_{\{T_{1}\leq t-t_{2}\}}|T_{2}=t_{2}))=\int_{0}^{\infty}\int_{0}^{t+t_{2}}\lambda^{2}e^{-\lambda (t_{1}+t_{2})}dt_{1}\,dt_{2}=1-\frac{e^{-\lambda t}}{2}$$.
This evaluates to
If $t<0$. Then
$$P(T\leq t)=\mathbb{E}(\mathbb{E}(\mathbf{1}_{\{T_{1}\leq t-t_{2}\}}|T_{2}=t_{2}))=\\\int_{0}^{\infty}\int_{0}^{\infty}\mathbf{1}_{\{t_{2}+t\geq 0,t_{1}\leq t_{2}+t\}}\lambda^{2}e^{-\lambda (t_{1}+t_{2})}dt_{1}\,dt_{2}=\\\int_{-t}^{\infty}\int_{0}^{t+t_{2}}\lambda^{2}e^{-\lambda (t_{1}+t_{2})}dt_{1}\,dt_{2}=\frac{1}{2}\cdot e^{\lambda t}$$.
So :-
$$\large F_{T}(t)=\begin{cases} 1-\frac{e^{-\lambda t}}{2}\quad, t\geq 0\\\frac{e^{\lambda t}}{2}\quad,t<0\end{cases}$$
The pdf can be found correspondingly by differentiating wrt $t$.
$$\large f_{T}(t)=\begin{cases} \frac{\lambda e^{-\lambda t}}{2}\quad, t\geq 0\\\frac{\lambda e^{\lambda t}}{2}\quad,t<0\end{cases}$$