Normal Distribution

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Normal Distribution

The well known bell shaped curve. According to the Central Limit Theorem, the probability density function of a large number of independent, identically distributed random numbers will approach the normal distribution. In the fractal family of distributions, the normal distribution only exists when alpha equals 2, or the Hurst exponent equals 0.50. Thus, the normal distribution is a special case which in time series analysis is quite rare. See: Alpha, Central Limit Theorem, Fractal Distribution.

Bell Curve

A curve on a chart in which most data points cluster around the median and become less frequent the farther they fall to either side of the median. When plotted on a chart, a bell curve looks roughly like a bell.
References in periodicals archive ?
The difference in percentage between observations will always have a skewed distribution, even for symmetrical normal distributions of the measurements (8).
The normal distribution describes the distribution of randomly occurring events when nothing intervenes.
Based on the results presented in Table 1, we cannot reject the hypothesis that GDP and Population follow a log normal distribution.
The truncated normal distribution is a probability distribution related to the normal distribution.
The first one is calculated assuming normal distribution of expected inflation and official current inflation as a measure of perceived inflation.
longitudinal data with observations < LOD for an analyte measured on two different occasions, or cross-sectional data with observations < LOD for two different analytes) can be imputed based on a bivariate normal distribution and analyzed using an MI approach.
The basic formula for VaR, assuming normal distribution of losses is presented below:
Each of the distributions listed in the first column, from which sample 1 was drawn, was paired with a normal distribution, from which sample 2 was drawn.
Figures 1-3 show examples of the frequent spectra which came from the normal distributions being affected by two, three, and four perturbing factors (the progression coefficients [q.
Bhattacharya's method for estimating parameters for a mixture of normal distributions is well described by Sparre & Venema (1992).
The values for kurtosis relate to leptokurtic distributions, which exhibit fat tails and high peaks with respect to normal distributions.
n]([mu], [summation]) for random vectors belonging to the class of multivariate Normal distributions with parameters [mu] and [summation].