Normal Distribution

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Related to Normal distributions: normal curve

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 size distributions of 20 main crystal types were approximated by single normal or log-normal distributions; however, in most cases the combination of two normal or log normal distributions was more suitable.
A random variable X has a two-piece normal distribution with parameters [Mu], [[Sigma].
8 In fact, the traditional jump diffusion model can be interpreted as allowing for the possibility of a jump between an infinite number of normal distributions (Kon [1984]).
To aid the user in making this assessment, the normal probability plot is plotted with a straight line corresponding to the normal distribution with the mean and variance estimated from the data.
Suppose that an element is chosen at random from a normal distribution for which the value of the mean |Theta~ is unknown (-|infinity~ |is less than~ |Theta~ |is less than~ |infinity~), and the value of the variance ||Sigma~.
In reviewing previous market events, such as the sovereign debt crisis in March 2010, the threat of potential losses was exposed with PerTrac RiskPlus, but normal distribution analytics continued with its overly optimistic market forecast despite the abundance of warning signs.
The normal distribution describes the distribution of randomly occurring events when nothing intervenes.
Likewise, the log-log plot of the density function for a log normal distribution is a straight line for a large part of the body.
and replacing parameters of the normal distribution with their definitions 20 and 21, the benchmark value is derived in the following way:
METHODS: We have presented the likelihood function for a bivariate normal distribution taking into account values < LOD as well as missing data assumed missing at random, and we use the estimated distributional parameters to impute values < LOD and to generate multiple plausible data sets for analysis by standard statistical methods.
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).