Let's consider a Poisson process on the line with rate parameter $\lambda$. There are two ways to think about this:
In any interval $[a,b)$ the expected number of events is distributed as a Poisson random variable with mean $\lambda(b-a)$. Conditional on the number of events, the times of the events in $[a,b)$ are uniformly random.
The inter-arrival times of events is exponential with mean $\lambda^{-1}$.
This is all well-explained on Wikipedia for example. (Well, point (2) is rather given short shrift).
Question 1: I would like to treat this equivalence in a (very) elementary manner. What would be a good textbook, or other resource, which covers this? Perhaps via simulation?
(I am teaching this as a "research / modelling" project, and so I cannot just write my own notes and/or set my own simulation tasks. Rather I really want/need to point the students to some existing resources.)
A perhaps harder question to answer is:
Question 2: I'd love a research article, example in a book, etc. which uses this equivalence in some way to model some real data.
Let me comment on this slightly: there are loads of examples (e.g. "phone calls to a helpline in a given hour") which are Poisson distributed. But I don't know of an example which treats this as a process (e.g. the initial data is presented as times of the calls, not already just as counts).