Section 2.6: Poisson Distribution

Counting events in continuous intervals

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Counting Random Events

A New Kind of Counting

Sometimes we count events that happen randomly in time or space:

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Phone calls arriving at a call center per hour

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Accidents at an intersection per month

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Typos on a page of text

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Radioactive particles detected per second

What Makes These Special?

  • Events occur independently of each other
  • Events occur at a constant average rate
  • Two events can't happen at exactly the same instant

Key Insight: Unlike the binomial (fixed number of trials), here we're counting events in a continuous interval where the count could theoretically be 0, 1, 2, 3, ... with no upper limit!