Other Distribution Models
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Other Distribution Models
There are myriad distributions to account for all sorts of problems and uncertainties. We will explain a few of these here, but feel free to ignore this part if you find it too technical. Another famous one is the Poisson distribution—so-called after the 19th century French mathematician, Simeon Denis Poisson—which is used to model the occurrence of rare events, like earthquakes. See Figure 5-3.
Figure 5-3: The Poisson distribution for different values of the parameter lambda
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Another popular distribution is the exponential distribution. This is a distribution of waiting times. If we are modeling the arrival of ambulances, we might ask how long will it take until the next ambulance arrives? See Figure 5-4.
Figure 5-4: Exponential distribution for different parameter settings
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Then there is the geometric distribution, which can tell us how many failures we will get until we reach a success. For example, how many times do I need to roll a die, until I roll a 6?
The binomial distribution describes the number of successes in a number of trials—for example, if I am betting on getting a 6 on a roll of a die, how many successes will I get if I roll the die 100 times?
