ems:NormalDistribution
Probability distributions:
ems:PointEstimate,
ems:UniformDistribution,
ems:TriangularDistribution,
ems:NormalDistribution,
ems:PoissonDistribution,
ems:QuantileFunction,
ems:CumulativeDistributionFunction
Description
The
normal distribution naturally occurs in many situations. When a measure is affected by many random factors, the result is a normal distribution under very general conditions (see the
Central Limit Theorem). For example, the total duration of a project depends on the durations of all the tasks. If there are many tasks and they their estimated durations are described by well-behaved probability distributions, then the estimated total duration is described by a normal distribution.
An ems:NormalDistribution resource represents a normal distribution.
Properties
An ems:NormalDistribution has the following properties
ems:mu
This required property is the mean of the distribution, traditionally denoted by the Greek letter mu.
ems:scale
This required property is the scale of the distribution, traditionally denoted by the Greek letter sigma. Its square is the variance of the distribution. This property MUST be positive.
Examples
Normal Distribution 1
The following resource represents a normal distribution with a mu value of 42 and a sigma value of 7:
Listing of Normal Distribution 1
<?xml version="1.0"?>
<ems:NormalDistribution xmlns:ems="http://open-services.net/ns/ems#"
xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#">
<ems:mu rdf:datatype="http://www.w3.org/2001/XMLSchema#double">42</ems:mu>
<ems:sigma rdf:datatype="http://www.w3.org/2001/XMLSchema#double">7</ems:sigma>
</ems:NormalDistribution>
Comments
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Topic revision: r6 - 24 Sep 2010 - 15:20:56 -
ArthurRyman