I have a hw question that says: Consider a Poisson counting process with arrival rate $λ = 1.$ Suppose it is observed that there is exactly one arrival in the time interval $[0,t_0).$ Find the PDF of that arrival time.
Can you help me understand what the question is asking! Is it just asking what is $P(N(t_0) = 1) = \lambda t_0 e^{-\lambda t_0}$ (because $P(N(t) = k) = (\lambda t)^k e^{-\lambda t}/k!$
I think this must mean the conditional p.d.f. of the arrival time given the event that there was exactly one arrival.
Let (capital) $T$ be the time of the first arrival; let $N(t)$ be the number of arrivals at or before time (lower-case) $t.$
Suppose $0\le t\le t_0.$
Then \begin{align} & \Pr(T\le t\mid N(t_0)=1) \\[8pt] = {} & \Pr( N(t_0)- N(t)=0\mid N(t_0)=1) \\[8pt] = {} &\frac{\Pr( N(t_0)-N(t)=0\ \&\ N(t_0)=1) }{\Pr(N(t_0)=1)} \\[8pt] = {} & \frac{\Pr( N(t)=1\ \&\ N(t_0) - N(t) =0)}{\Pr(N(t_0)=1)} \\[8pt] = {} & \frac{\Big(e^{-t\lambda} (t\lambda)^1/1!\Big) \cdot \Big(e^{-\lambda(t_0-t)} (\lambda(t_0-t))^0/0!\Big)}{e^{-\lambda t_0} (\lambda t_0)^1/1!} \\[8pt] = {} & t/t_0. \end{align} This is the c.d.f. Differentiate to get the p.d.f. Then you see that the conditional distribution of the arrival time, given that there was exactly one arrival, is uniform in the interval $[0,t_0).$
PS: Notice that the bottom-line answer is the same regardless of which positive number $\lambda$ is.