NormalDistribution Class

[SerializableAttribute]
public class NormalDistribution : ContinuousDistribution

<SerializableAttribute>
Public Class NormalDistribution
	Inherits ContinuousDistribution

[SerializableAttribute]
public ref class NormalDistribution : public ContinuousDistribution

[<SerializableAttribute>]
type NormalDistribution =  
    class
        inherit ContinuousDistribution
    end

The NormalDistribution type exposes the following members.

	Name	Description
	NormalDistribution	Constructs a new NormalDistribution with mean equal to zero and standard deviation equal to 1.
	NormalDistribution(Double)	Constructs a new NormalDistribution with specified mean and standard deviation equal to 1.
	NormalDistribution(VectorDouble)	Estimates the parameters of the distribution of a variable assuming it follows a normal distribution.
	NormalDistribution(Double, Double)	Constructs a new NormalDistribution with specified mean and standard deviation.
	NormalDistribution(VectorDouble, EstimationMethod)	Estimates the parameters of the distribution of a variable assuming it follows a normal distribution.

	Name	Description
	Entropy	Gets the entropy of the distribution. (Overrides DistributionEntropy.)
	InterQuartileRange	Returns the inter-quartile range of this distribution. (Inherited from ContinuousDistribution.)
	IsSymmetrical	Gets whether the distribution is known to be symmetrical around the mean. (Overrides ContinuousDistributionIsSymmetrical.)
	IsUnimodal	Gets whether the distribution has one or more modes. (Inherited from ContinuousDistribution.)
	Kurtosis	Gets the kurtosis of the distribution. (Overrides DistributionKurtosis.)
	Mean	Gets the mean or expectation value of the distribution. (Overrides DistributionMean.)
	Median	Gets the median of the distribution. (Overrides ContinuousDistributionMedian.)
	Mode	Gets the mode of the distribution. (Overrides ContinuousDistributionMode.)
	NumberOfModes	Gets the number of modes of the distribution. (Inherited from ContinuousDistribution.)
	Skewness	Gets the skewness of the distribution. (Overrides DistributionSkewness.)
	StandardDeviation	Gets the standard deviation of the distribution. (Overrides DistributionStandardDeviation.)
	StatisticSymbol	Gets the common symbol to describe a statistic from the distribution. (Overrides DistributionStatisticSymbol.)
	Support	Gets the support of the distribution. (Inherited from ContinuousDistribution.)
	Variance	Gets the variance of the distribution. (Overrides DistributionVariance.)

	Name	Description
	Cdf	Evaluates the cumulative distribution function (CDF) of this distribution for the specified value. (Inherited from ContinuousDistribution.)
	DistributionFunction(Double)	Evaluates the cumulative distribution function (CDF) of this distribution for the specified value. (Overrides ContinuousDistributionDistributionFunction(Double).)
	DistributionFunction(Double, Double, Double)	Evaluates the cumulative distribution function (CDF) of this distribution for the specified value.
	Equals	Determines whether the specified object is equal to the current object. (Inherited from Object.)
	Finalize	Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection. (Inherited from Object.)
	GetAllModes	Returns an array that contains all the modes of the distribution. (Inherited from ContinuousDistribution.)
	GetConfidenceInterval	Returns a confidence interval at the specified level.
	GetExpectationValue(FuncDouble, Double)	Returns the expectation value of a function. (Inherited from ContinuousDistribution.)
	GetExpectationValue(FuncDouble, Double, Double, Double)	Returns the un-normalized expectation value of a function over the specified interval. (Inherited from ContinuousDistribution.)
	GetExpectedHistogram(Double, Double)	Gets a vector containing a histogram of the expected number of samples for a given total number of samples. (Inherited from ContinuousDistribution.)
	GetExpectedHistogram(IntervalIndexDouble, Double)	Gets a vector containing a histogram of the expected number of samples for a given total number of samples. (Inherited from ContinuousDistribution.)
	GetExpectedHistogram(Double, Double, Int32, Double)	Gets a vector whose bins contain the expected number of samples for a given total number of samples. (Inherited from ContinuousDistribution.)
	GetHashCode	Serves as the default hash function. (Inherited from Object.)
	GetRandomSequence	Returns a sequence of random samples from the distribution. (Inherited from ContinuousDistribution.)
	GetRandomSequence(Random)	Returns a sequence of random samples from the distribution. (Inherited from ContinuousDistribution.)
	GetRandomSequence(Random, Int32)	Returns a sequence of random samples of the specified length from the distribution. (Inherited from ContinuousDistribution.)
	GetType	Gets the Type of the current instance. (Inherited from Object.)
	HazardFunction	Returns the probability of failure at the specified value. (Inherited from ContinuousDistribution.)
	InverseCdf	Returns the inverse of the DistributionFunction(Double). (Inherited from ContinuousDistribution.)
	InverseDistributionFunction(Double)	Returns the sample value at the specified percentile. (Overrides ContinuousDistributionInverseDistributionFunction(Double).)
	InverseDistributionFunction(Double, Double, Double)	Returns the inverse of the DistributionFunction(Double).
	LeftTailProbability	Returns the probability that a sample from the distribution is less than the specified value. (Inherited from ContinuousDistribution.)
	LogProbabilityDensityFunction	Returns the logarithm of the probability density function (PDF) of this distribution for the specified value. (Overrides ContinuousDistributionLogProbabilityDensityFunction(Double).)
	MemberwiseClone	Creates a shallow copy of the current Object. (Inherited from Object.)
	MomentFunction	Returns the value of the moment function of the specified order. (Overrides ContinuousDistributionMomentFunction(Int32, Double).)
	Pdf	Returns the value of the probability density function (PDF) of this distribution for the specified value. (Inherited from ContinuousDistribution.)
	Probability	Returns the probability that a sample taken from the distribution lies inside the specified interval. (Inherited from ContinuousDistribution.)
	ProbabilityDensityFunction	Returns the value of the probability density function (PDF) of this distribution for the specified value. (Overrides ContinuousDistributionProbabilityDensityFunction(Double).)
	RightTailProbability	Returns the probability that a sample from the distribution is larger than the specified value. (Inherited from ContinuousDistribution.)
	Sample	Returns a random sample from the distribution. (Inherited from ContinuousDistribution.)
	Sample(Int32)	Returns a vector of random samples from the distribution. (Inherited from ContinuousDistribution.)
	Sample(Random)	Returns a random sample from the distribution. (Overrides ContinuousDistributionSample(Random).)
	Sample(Int32, Random)	Returns a vector of random samples from the distribution. (Inherited from ContinuousDistribution.)
	Sample(Random, Double)	Returns a single random sample from a normal distribution with specified mean and standard deviation equal to 1.
	Sample(Random, Double, Double)	Returns a single random sample from a normal distribution with the specified parameters.
	SampleInto(Random, IListDouble)	Fills a list with random numbers from the distribution. (Inherited from ContinuousDistribution.)
	SampleInto(Random, IListDouble, Int32, Int32)	Fills part of a list with random numbers from the distribution. (Overrides ContinuousDistributionSampleInto(Random, IListDouble, Int32, Int32).)
	SurvivorDistributionFunction	Evaluates the survivor distribution function (SDF) of this distribution for the specified value. (Inherited from ContinuousDistribution.)
	ToString	Returns a string that represents the current object. (Overrides ObjectToString.)
	TwoTailedProbability	Returns the probability that a sample from the distribution deviates from the mean more than the specified value. (Inherited from ContinuousDistribution.)
	ZScore	Returns the z-score of a sample.

	Name	Description
	Standard	Represents the standard NormalDistribution.

Normal distributions are a family of distributions that have the same general shape. They are symmetric with outcomes more concentrated in the middle than in the tails. Normal distributions are sometimes described as bell shaped.

The Mean of the distribution acts as the location parameter. The standard deviation (which equals the square root of the ) acts as the scale parameter. The normal distribution does not have a shape parameter.

Reference