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 ?
Rather than treating the slope parameters in a linear fashion, the marginal effect of each explanatory variable can be calculated using the cumulative standard normal distribution in the case of the probit model or the cumulative exponential function for logit analysis.
In what follows we will prove that the joint distribution of the (properly rescaled) height and area variables in this ensemble converge in distribution to the two-dimensional standard normal distribution.
Summing up the who, the distribution obtained with t = x - a/[sigma] changing variables is called standard normal distribution.
where r is the risk free interest rate, t is the time until expiration of the option, and [PHI] is the standard normal distribution function.
The critical z value is a percentile of the standard normal distribution and is obtained from a standard normal table.
While the math can be a little complicated, the analysis is based upon the assumption that production per year is shaped like the standard normal distribution function.

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