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Probability distributions: ems:PointEstimate, ems:UniformDistribution, ems:TriangularDistribution, ems:NormalDistribution, ems:PoissonDistribution, ems:QuantileFunction, ems:CumulativeDistributionFunction


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.


An ems:NormalDistribution has the following properties

Property Range Type Occurrence Edits Description
ems:mu datatype xsd:double exactly-one read-write The mean of the distribution.
ems:sigma datatype xsd:double exactly-one read-write The scale of the distribution.


This required property is the mean of the distribution, traditionally denoted by the Greek letter mu.


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.


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=""
   <ems:mu rdf:datatype="">42</ems:mu>
   <ems:sigma rdf:datatype="">7</ems:sigma>


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Topic revision: r6 - 24 Sep 2010 - 15:20:56 - ArthurRyman
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