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 ?
It is obvious that any probability calculation related to a normally distributed random variable, can be accomplished by using one of the following three types of probabilities or some combination of those three:
However, the binomial and OLS regressions fit the distribution poorly because predictions were concentrated around the mean, and residuals were not normally distributed, as expected.
For example, it can be assumed that growth is normally distributed around 2 percent.
Furthermore, the LEP scores are normally distributed as a consequence of the central limit theorem and thus strengthen the evidence that the LEP resulted from a linear combination of multiple variables.
Scores were normally distributed around the mean for men (Kolmogorov-Smirnov test: df = 11, statistic =.
As compared to a virgin product, where these properties are more normally distributed, an interpretation of the skewness means that one must be concerned with significantly lower Izod impact performance, lower HDT performance, and higher MVR performance.
a) Normally Distributed, the value of the Test Statistic, Z*, is given by:
Normally distributed data were given as mean[+ or -]SD; * non-normally distributed data were given as median (minimum-maximum).
Indeed, a glance at historical price movements shows the flaws of assuming oil price movements are normally distributed.
If you choose 33 percentile, then 33% of the cells will have that color icon even if the values aren't normally distributed between the minimum and maximum values.
So this is the familiar problem we know that spreads are not normally distributed.