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DescriptiveAnalysis Class
Descriptive statistics analysis.
Inheritance Hierarchy
SystemObject
  Accord.Statistics.AnalysisDescriptiveAnalysis

Namespace:  Accord.Statistics.Analysis
Assembly:  Accord.Statistics (in Accord.Statistics.dll) Version: 3.8.0
Syntax
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[SerializableAttribute]
public class DescriptiveAnalysis : IMultivariateAnalysis, 
	IAnalysis, IDescriptiveLearning<DescriptiveAnalysis, double[]>
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The DescriptiveAnalysis type exposes the following members.

Constructors
  NameDescription
Public methodDescriptiveAnalysis
Constructs the Descriptive Analysis.
Public methodDescriptiveAnalysis(Double) Obsolete.
Constructs the Descriptive Analysis.
Public methodDescriptiveAnalysis(Double) Obsolete.
Constructs the Descriptive Analysis.
Public methodDescriptiveAnalysis(Double) Obsolete.
Constructs the Descriptive Analysis.
Public methodDescriptiveAnalysis(String)
Constructs the Descriptive Analysis.
Public methodDescriptiveAnalysis(Double, String) Obsolete.
Constructs the Descriptive Analysis.
Public methodDescriptiveAnalysis(Double, String) Obsolete.
Constructs the Descriptive Analysis.
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Properties
  NameDescription
Public propertyArray Obsolete.
Gets the source matrix from which the analysis was run.
Public propertyColumnNames
Gets the column names from the variables in the data.
Public propertyConfidence
Gets the 95% confidence intervals for the Means.
Public propertyCorrelationMatrix
Gets the Correlation Matrix
Public propertyCovarianceMatrix
Gets the Covariance Matrix
Public propertyDeviance
Gets the 95% deviance intervals for the Means.
Public propertyDeviationScores
Gets the mean subtracted data.
Public propertyDistinct
Gets a vector containing the number of distinct elements for each data column.
Public propertyInnerFences
Gets an array containing the inner fences of each data column.
Public propertyKurtosis
Gets an array containing the kurtosis for of each data column.
Public propertyLazy
Gets or sets whether the properties of this class should be computed only when necessary. If set to true, a copy of the input data will be maintained inside an instance of this class, using more memory.
Public propertyMeans
Gets a vector containing the Mean of each data column.
Public propertyMeasures
Gets a collection of DescriptiveMeasures objects that can be bound to a DataGridView.
Public propertyMedians
Gets a vector containing the Median of each data column.
Public propertyModes
Gets a vector containing the Mode of each data column.
Public propertyOuterFences
Gets an array containing the outer fences of each data column.
Public propertyQuantileMethod
Gets or sets the method to be used when computing quantiles (median and quartiles).
Public propertyQuartiles
Gets an array containing the interquartile range of each data column.
Public propertyRanges
Gets an array containing the Ranges of each data column.
Public propertySamples
Gets the number of samples (or observations) in the data.
Public propertySkewness
Gets an array containing the skewness for of each data column.
Public propertySource Obsolete.
Gets the source matrix from which the analysis was run.
Public propertyStandardDeviations
Gets a vector containing the Standard Deviation of each data column.
Public propertyStandardErrors
Gets a vector containing the Standard Error of the Mean of each data column.
Public propertyStandardScores
Gets the mean subtracted and deviation divided data. Also known as Z-Scores.
Public propertySums
Gets an array containing the sum of each data column.
Public propertyVariables
Gets the number of variables (or features) in the data.
Public propertyVariances
Gets a vector containing the Variance of each data column.
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Methods
  NameDescription
Public methodCompute Obsolete.
Computes the analysis using given source data and parameters.
Public methodEquals
Determines whether the specified object is equal to the current object.
(Inherited from Object.)
Protected methodFinalize
Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection.
(Inherited from Object.)
Public methodGetConfidenceInterval
Gets a confidence interval for the Means within the given confidence level percentage.
Public methodGetDevianceInterval
Gets a deviance interval for the Means within the given confidence level percentage (i.e. uses the standard deviation rather than the standard error to compute the range interval for the variable).
Public methodGetHashCode
Serves as the default hash function.
(Inherited from Object.)
Public methodGetType
Gets the Type of the current instance.
(Inherited from Object.)
Public methodLearn
Learns a model that can map the given inputs to the desired outputs.
Protected methodMemberwiseClone
Creates a shallow copy of the current Object.
(Inherited from Object.)
Public methodToString
Returns a string that represents the current object.
(Inherited from Object.)
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Extension Methods
  NameDescription
Public Extension MethodHasMethod
Checks whether an object implements a method with the given name.
(Defined by ExtensionMethods.)
Public Extension MethodIsEqual
Compares two objects for equality, performing an elementwise comparison if the elements are vectors or matrices.
(Defined by Matrix.)
Public Extension MethodTo(Type)Overloaded.
Converts an object into another type, irrespective of whether the conversion can be done at compile time or not. This can be used to convert generic types to numeric types during runtime.
(Defined by ExtensionMethods.)
Public Extension MethodToTOverloaded.
Converts an object into another type, irrespective of whether the conversion can be done at compile time or not. This can be used to convert generic types to numeric types during runtime.
(Defined by ExtensionMethods.)
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Remarks

Descriptive statistics are used to describe the basic features of the data in a study. They provide simple summaries about the sample and the measures. Together with simple graphics analysis, they form the basis of virtually every quantitative analysis of data.

This class can also be bound to standard controls such as the DataGridView by setting their DataSource property to the analysis' Measures property.

References:

  • Wikipedia, The Free Encyclopedia. Descriptive Statistics. Available on: http://en.wikipedia.org/wiki/Descriptive_statistics

Examples
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// Suppose we would like to compute descriptive
// statistics from the following data samples:
double[][] data =
{
    new double[] { 1, 52, 5 },
    new double[] { 2, 12, 5 },
    new double[] { 1, 65, 5 },
    new double[] { 1, 25, 5 },
    new double[] { 2, 62, 5 },
};

// Create the descriptive analysis
var analysis = new DescriptiveAnalysis();

// Learn the data
analysis.Learn(data);

// Query different measures
double[] means = analysis.Means;
double[] variance = analysis.Variances;
DoubleRange[] quartiles = analysis.Quartiles;
See Also