使用准则:

double average = someDoubles.Average();
double sumOfSquaresOfDifferences = someDoubles.Select(val => (val - average) * (val - average)).Sum();
double sd = Math.Sqrt(sumOfSquaresOfDifferences / someDoubles.Length); 

<代码>d变量将具有标准偏差。

如果有<代码>List<double>,则使用<代码>一些Doubles。 代码上最后一行的而不是susles.Length。

To calculate standard deviation you can use this code. Taken directly from Calculate Standard Deviation of Double Variables in C# by Victor Chen.

private double getStandardDeviation(List<double> doubleList)  
{  
   double average = doubleList.Average();  
   double sumOfDerivation = 0;  
   foreach (double value in doubleList)  
   {  
      sumOfDerivation += (value) * (value);  
   }  
   double sumOfDerivationAverage = sumOfDerivation / (doubleList.Count - 1);  
   return Math.Sqrt(sumOfDerivationAverage - (average*average));  
}  

http://www.victorchen.info/calculate-standard-deviation-of-double-variables-in-c/“rel=“noreferer”>link to Victor ssite已不再可行,但仍包括帮助维持归属。

鉴于外人,你可能会发现interquarless range比标准偏离更为有用。 比较简单,可以计算:仅仅区分数字,在75%和25%的基数中找到数值的区别。

你在计算标准偏差方面已经有了一些很好的答案,但我要补充。 计算清单差异的Knuth s算法。 Knuth s algo在数据上用单一发照进行计算。 如上文所述,标准偏离只是差异的内在根源。 第Knus算法还允许你计算差异的中间值,如果这证明有用的话。

If you are on .NET 4.0 next links can be helpful
Standard Deviation in LINQ
http://msdn.microsoft.com/en-us/library/dd456873.aspx

在VB。 Net, Code for Standard Deviation, Z-Score, and NormSDist. 我删除并沿用了工作守则,并修改了该守则,使之更为笼统。 我本可以提出问题。 此外,我还不是听说过的。

Public Property SumOfSquaresOfDifferences As Double   calculated elsewhere

Public ReadOnly Property StdOfTotalMatches As Double
    Get
        If NumberOfTickets = 0 Then Return 0
        Return Math.Sqrt(SumOfSquaresOfDifferences / NumberOfTickets)
    End Get
End Property

Public ReadOnly Property zScoreOfTotalMatches As Double
    Get
        If StdOfTotalMatches = 0 Then Return 0
        Return (TotalMatches / NumberOfTickets - AverageMatches) / StdOfTotalMatches
    End Get
End Property

Public ReadOnly Property NormSDistOfTotalMatches As Double
    Get
        Return NormSDist(zScoreOfTotalMatches)
    End Get
End Property

Public ReadOnly Property AverageMatches As Double
    Get
        Return If(NumberOfTickets, TotalMatches / NumberOfTickets, 0)
    End Get
End Property

Shared Function NormSDist(ByVal zScore As Double) As Double
    Dim ErfResult As Double = Erf(zScore / Math.Sqrt(2.0))
    Dim res As Double = ErfResult + (1 - ErfResult) / 2
    Return If(zScore < 0, 1 - res, res)
End Function

Shared Function Erf(ByVal n As Double) As Double

    Dim t As Double = 1.0 / (1.0 + 0.5 * Math.Abs(n))

      use Horner s method - thanks to http://bytes.com/topic/c-sharp/answers/240995-normal-distribution
    Dim d As Double = 1 - t * Math.Exp(-n * n - 1.26551223 + _
    t * (1.00002368 + _
    t * (0.37409196 + _
    t * (0.09678418 + _
    t * (-0.18628806 + _
    t * (0.27886807 + _
    t * (-1.13520398 + _
    t * (1.48851587 + _
    t * (-0.82215223 + _
    t * (0.17087277))))))))))

     Return If(d >= 0, d, 1 - d)
    Return d

End Function