The art of computer programming, volume 2 (3rd ed.): seminumerical algorithms
The art of computer programming, volume 2 (3rd ed.): seminumerical algorithms
Atlas for Computing Mathematical Functions: An Illustrated Guide for Practitioners with Programs in FORTRAN and Mathematica with Cdrom
Computing in Science and Engineering
Computing in Science and Engineering
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We scientists and engineers often use Poisson's probability distribution to characterize the statistics of rare events whose average number is small. Using it correctly is crucial if we are to validate claims of discovery of new phenomena, such as a new fundamental particle (few candidate collision events among millions), a remote galaxy (few photons in the telescope among the billions emitted), or brain damage from using cell phones (few tumors among millions of users). In risk assessment, such as estimating the chance of dying from a horse kick if you're in the Prussian army or from suicide (two of its early uses), it plays a crucial role, which should interest actuaries as well as morticians. I've noticed that the Poisson distribution is often misunderstood and misapplied, so in this column I'll describe some of its interesting and relevant properties.