normal distribution

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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:
 Noun 1 normal distribution - a theoretical distribution with finite mean and varianceGaussian distributiondistribution, statistical distribution - (statistics) an arrangement of values of a variable showing their observed or theoretical frequency of occurrencestatistics - 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 ?
We choose only the variance from a fixed number of studies when the [Z.sub.i] are drawn from a half normal distribution HN(0,1).
Unfortunately, unless the sample sizes within sites are enormous (e.g., &gt;1,000), the shape of the distribution of estimates is dominated by the normal distribution as a result of imperfect reliability in site-specific estimates.
Normal or Gaussian distribution is one of the most used statistical distributions, and most statistical methods accept the hypothesis of normal distribution of data.
It is urgent to ensure delivery to ensure normal distribution to families." Some 9 percent of those interviewed reported begging for assistance, a rise from 5 percent in March, Byrs said.
However, on theoretical grounds, one could argue that the normal distribution is appropriate.
and replacing parameters of the normal distribution with their definitions 20 and 21, the benchmark value is derived in the following way:
of a hundred observations from the normal distribution
Pacey [1] first studied the diffusion problem and proposed a model assuming that the speed follows normal distribution ranging from negative to positive infinity.
[7-9] state that the measurements of nanofibres diameter are distributed by log normal distribution. Dosunmu et al.
Jordan (1869) claimed improved precision of G over Gauss's root mean square estimator for normal distribution. According to Von Andrae (1872) the asymptotic efficiency of G relative to S is 97.8% for normally distributed data and G, given its much simpler calculation, is a serious competitor to the usually preferred S.
where [u.sub.[alpha]]--the value of the random variable U with a standardized normal distribution, as designated for a given confidence coefficient 1-[alpha] from an array of a normal distribution, s--sample standard deviation as calculated according to the relation [6-8]

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