normal distribution

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Related to Normal random variable: Standard normal distribution, normal distribution

normal distribution

n.
A theoretical frequency distribution for a random variable, characterized by a bell-shaped curve symmetrical about its mean. Also called Gaussian distribution.

normal distribution

n
(Statistics) statistics a continuous distribution of a random variable with its mean, median, and mode equal, the probability density function of which is given by (exp-[(x–μ)2/2σ2]/σ√(2π)) where μ is the mean and σ2 the variance. Also called: Gaussian distribution

nor′mal distribu′tion


n.
a theoretical frequency distribution represented by a normal curve. Also called Gaussian distribution.
ThesaurusAntonymsRelated WordsSynonymsLegend:
Noun1.normal distribution - a theoretical distribution with finite mean and variance
distribution, statistical distribution - (statistics) an arrangement of values of a variable showing their observed or theoretical frequency of occurrence
statistics - a branch of applied mathematics concerned with the collection and interpretation of quantitative data and the use of probability theory to estimate population parameters
References in periodicals archive ?
[mu] and [sigma] are the mean and standard deviation of the normal random variable. N is the quadrature order (equal to the number of Gauss point).
where [phi] is the fixed intercept and represents the initial degradation, and [beta] is a normal random variable such that the mean of [beta] is [[mu].sub.1] and the variance of [beta] is [[sigma].sup.2.sub.1].
Generation of a Normal random variable, N([mu],[sigma]), [mu] [member of] R, [sigma] > 0, whose pdf is given by (1.10).
Caption: Figure 1 Confidence Level q Required to Eliminate the Residual Estimation Risk for a Normal Random Variable With Known Scale Parameter and Risk Measure [TVaR.sub.p]
In this paper the unity of cumulative distribution function is divided to two parts using cumulative distribution function under and above the mean to obtain a measure of skewness that is zero for symmetric distributions and to three parts in terms of 50% confidence interval of normal random variable to obtain a measure of data-concentration that is zero for normal distribution.
where [[phi].sup.-1] represents the inverse CDF of a standard normal random variable. u are independent uniform random variables from the interval [0,1].
[18] studied generalization of Tukey's g-h family of distributions, when the standard normal random variable is replaced by a continuous random variable U with mean 0 and variance 1.
Session 8 gives the steps for generating normal distributions and computing area under the normal curve for any normal random variable. Session 9 simulates drawing many random samples from populations whose distributions are known.
The misalignment angle can be modeled by a normal random variable [psi] with standard deviation [[sigma].sub.[psi]].
Since [U.sub.i] is a normal random variable for all i, [U.sub.1] + [U.sub.2] + [U.sub.3] is also normally distributed.
On the other hand, u i is a non-negative truncated half normal random variable associated with farm-specific factors that lead to not attaining maximum efficiency of production in ith firm; u i is associated with technical inefficiency of the farm and ranges between zero and one.