|   | MeasuresStandardDeviation Method (Double, Double, Boolean) | 
        
         
              Calculates the matrix Standard Deviations vector.
            
 
    Namespace: 
   Accord.Statistics
    Assembly:
   Accord.Math (in Accord.Math.dll) Version: 3.8.0
 Syntax
Syntaxpublic static double[] StandardDeviation(
	this double[][] matrix,
	double[] means,
	bool unbiased = true
)
<ExtensionAttribute>
Public Shared Function StandardDeviation ( 
	matrix As Double()(),
	means As Double(),
	Optional unbiased As Boolean = true
) As Double()
Parameters
- matrix
- Type: SystemDouble
 A matrix whose deviations will be calculated.
- means
- Type: SystemDouble
 The mean vector containing already calculated means for each column of the matrix.
- unbiased (Optional)
- Type: SystemBoolean
 Pass true to compute the standard deviation using the sample variance.
              Pass false to compute it using the population variance. See remarks
              for more details.
Return Value
Type: 
DoubleReturns a vector containing the standard deviations of the given matrix.
Usage Note
In Visual Basic and C#, you can call this method as an instance method on any object of type . When you use instance method syntax to call this method, omit the first parameter. For more information, see 
Extension Methods (Visual Basic) or 
Extension Methods (C# Programming Guide).
 Remarks
Remarks
                Setting unbiased to true will make this method 
                compute the standard deviation σ using the sample variance, which is an unbiased 
                estimator of the true population variance. Setting this parameter to true will
                thus compute σ using the following formula:
                   N
σ² = 1 / (N - 1)  ∑   (x_i − μ)²
                   i=1
                Setting unbiased to false will assume the given values
                already represent the whole population, and will compute the population variance
                using the formula: 
                   N
σ² =   (1 / N)    ∑   (x_i − μ)²
                   i=1 See Also
See Also