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Percentile50(Series,ElementValue) Method
See Also 
dotnetCHARTING Namespace > FinancialEngine Class > Percentile50 Method : Percentile50(Series,ElementValue) Method


s
A financial series.
elementValue
Specifies the particular element value (for example High, Low, Close or Open of the financial time series) which will be considered within this indicator evaluation. In particular, if you wish to use the element value high then you should pass the parameter High. In a similarly fashion if you wish to use the low, close or open, then you should pass the parameter Low, Close, Open, respectively.
Calculates the second percentile of the series.

Syntax

Visual Basic (Declaration)  
Public Overloads Shared Function Percentile50( _
   ByVal s As Series, _
   ByVal elementValue As ElementValue _
) As Element
Visual Basic (Usage) Copy Code
Dim s As Series
Dim elementValue As ElementValue
Dim value As Element
 
value = FinancialEngine.Percentile50(s, elementValue)
C#  
public static Element Percentile50( 
   Series s,
   ElementValue elementValue
)

Parameters

s
A financial series.
elementValue
Specifies the particular element value (for example High, Low, Close or Open of the financial time series) which will be considered within this indicator evaluation. In particular, if you wish to use the element value high then you should pass the parameter High. In a similarly fashion if you wish to use the low, close or open, then you should pass the parameter Low, Close, Open, respectively.

Remarks

Recall that the percentile is the value such that at least interest-percent of the data set items are less than or equal to this value, or equivalently if at least (100-interest) percent of the items are greater than or equal to this value.

Remarks:

  1. The 50-th percentile is the measure of centrality of a data set known as the median. The median can also be evaluated using Median.
  2. The 25-th, 50-th, 75-th percentiles are often referred to as the 1-st, 2-nd (median) and 3-rd quartile respectively. The term quartile refers to the fact that these three values will roughly divide the data set considered into four equal parts.

See Also