Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
8940940 | Journal d'imagerie diagnostique et interventionnelle | 2017 | 5 Pages |
Abstract
In probability theory, the normal (or Gaussian) distribution is a common continuous probability distribution. Normal distributions are important in statistics and are often used in medicine to represent real-valued random variables, which distributions are not known. The normal distribution is associated with the central limit theorem. In its most general form, under some conditions (which include finite variance), this theorem states that averages of samples of observations of random variables independently drawn from independent distributions converge in distribution to the normal when the number of observations is sufficiently large. This article presents what a radiologist has to know on this distribution.
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Authors
P. Ingrand,