DescriptiveAnalysis Class 
Namespace: Accord.Statistics.Analysis
[SerializableAttribute] public class DescriptiveAnalysis : IMultivariateAnalysis, IAnalysis, IDescriptiveLearning<DescriptiveAnalysis, double[]>
The DescriptiveAnalysis type exposes the following members.
Name  Description  

DescriptiveAnalysis 
Constructs the Descriptive Analysis.
 
DescriptiveAnalysis(Double)  Obsolete.
Constructs the Descriptive Analysis.
 
DescriptiveAnalysis(Double)  Obsolete.
Constructs the Descriptive Analysis.
 
DescriptiveAnalysis(Double)  Obsolete.
Constructs the Descriptive Analysis.
 
DescriptiveAnalysis(String) 
Constructs the Descriptive Analysis.
 
DescriptiveAnalysis(Double, String)  Obsolete.
Constructs the Descriptive Analysis.
 
DescriptiveAnalysis(Double, String)  Obsolete.
Constructs the Descriptive Analysis.

Name  Description  

Array  Obsolete.
Gets the source matrix from which the analysis was run.
 
ColumnNames 
Gets the column names from the variables in the data.
 
Confidence 
Gets the 95% confidence intervals for the Means.
 
CorrelationMatrix 
Gets the Correlation Matrix
 
CovarianceMatrix 
Gets the Covariance Matrix
 
Deviance 
Gets the 95% deviance intervals for the Means.
 
DeviationScores 
Gets the mean subtracted data.
 
Distinct 
Gets a vector containing the number of distinct elements for each data column.
 
InnerFences 
Gets an array containing the inner fences of each data column.
 
Kurtosis 
Gets an array containing the kurtosis for of each data column.
 
Lazy 
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.
 
Means 
Gets a vector containing the Mean of each data column.
 
Measures 
Gets a collection of DescriptiveMeasures objects that can be bound to a DataGridView.
 
Medians 
Gets a vector containing the Median of each data column.
 
Modes 
Gets a vector containing the Mode of each data column.
 
OuterFences 
Gets an array containing the outer fences of each data column.
 
QuantileMethod 
Gets or sets the method to be used when computing quantiles (median and quartiles).
 
Quartiles 
Gets an array containing the interquartile range of each data column.
 
Ranges 
Gets an array containing the Ranges of each data column.
 
Samples 
Gets the number of samples (or observations) in the data.
 
Skewness 
Gets an array containing the skewness for of each data column.
 
Source  Obsolete.
Gets the source matrix from which the analysis was run.
 
StandardDeviations 
Gets a vector containing the Standard Deviation of each data column.
 
StandardErrors 
Gets a vector containing the Standard Error of the Mean of each data column.
 
StandardScores 
Gets the mean subtracted and deviation divided data. Also known as ZScores.
 
Sums 
Gets an array containing the sum of each data column.
 
Variables 
Gets the number of variables (or features) in the data.
 
Variances 
Gets a vector containing the Variance of each data column.

Name  Description  

Compute  Obsolete.
Computes the analysis using given source data and parameters.
 
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.)  
GetConfidenceInterval 
Gets a confidence interval for the Means
within the given confidence level percentage.
 
GetDevianceInterval 
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).
 
GetHashCode  Serves as the default hash function. (Inherited from Object.)  
GetType  Gets the Type of the current instance. (Inherited from Object.)  
Learn 
Learns a model that can map the given inputs to the desired outputs.
 
MemberwiseClone  Creates a shallow copy of the current Object. (Inherited from Object.)  
ToString  Returns a string that represents the current object. (Inherited from Object.) 
Name  Description  

HasMethod 
Checks whether an object implements a method with the given name.
(Defined by ExtensionMethods.)  
IsEqual 
Compares two objects for equality, performing an elementwise
comparison if the elements are vectors or matrices.
(Defined by Matrix.)  
To(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.)  
ToT  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.) 
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:
// 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;