The normaldistribution was first introduced by de Moivre in an article in 1733 (reprinted in the second edition of his The Doctrine of Chances, 1738) in the context of approximating certain binomial distributions for large n.

In that case, the assumption of normality is not justified, and it is the logarithm of the variable of interest that is normallydistributed.

The derivation of the maximum-likelihood estimator of the covariance matrix of a multivariate normaldistribution is perhaps surprisingly subtle and elegant.

In probability theory and statistics, a multivariate normaldistribution, also sometimes called a multivariate Gaussian distribution (in honor of Carl Friedrich Gauss, who was not the first to write about the normaldistribution) is a specific probability distribution.

The cumulative distribution function (cdf) F ( x) is defined as the probability that all values in a random vector X are less than or equal to the corresponding values in vector x.

Two random variables that are normallydistributed may fail to be jointly normallydistributed, i.e., the vector whose components they are may fail to have a multivariate normaldistribution.

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