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Statistics · Chapter 6

Poisson and Geometric

The binomial needed a fixed number of trials. These two do not. A Poisson variable counts how many events land in a window of time or space; a geometric variable counts how many trials you run until the first success. Same toolkit, two very different questions — drag the parameter and watch each one answer its own.

Poisson (λ = 4.0)

P(X = k) in the highlighted region k itself simulated the mean μ

Which one is it?

Before any formula, decide what is being counted. That single question picks the distribution.

Poisson

“How many, in this window?”
  • Counts events, not trials — there are no trials to count.
  • Needs a fixed interval: an hour, a page, a square metre.
  • Events arrive one at a time, independently, at a constant average rate.
  • X can be 0, and has no upper limit.
  • One parameter: λ, the mean count per interval.

Geometric

“How long until the first one?”
  • Counts trials, and you stop at the first success.
  • Trials are independent, each with the same success chance p.
  • X is at least 1 — the successful trial is counted — and has no upper limit.
  • The number of trials is not decided in advance; that is what makes it not binomial.
  • One parameter: p.
And for contrast, the binomial from the previous section answers a third question — “in a fixed number of trials n, how many succeeded?” If n is pinned down in advance, it is binomial; if you are counting events in a window it is Poisson; if you are counting trials until the first success it is geometric.
Poisson (λ = 4.0)drag the slider below
The one parameter
4.0
Mean μ4.00= λ
SD σ2.00= √λ
Most likely value4 
Skew0.50 
Try a real situation
Read a probability off the chart
4

Does it actually happen that way?

Repetitions0 
Observed mean—theory 4.00
Observed SD—theory 2.00