Verify distribution uniformity/Chi-squared test: Difference between revisions
Verify distribution uniformity/Chi-squared test (view source)
Revision as of 15:41, 28 December 2018
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distribution "4 21461 0 522573 1 244456 2 139979 3 71531" assessed as unfair</pre>
=={{header|VBA}}==
The built in worksheetfunction ChiSq_Dist of Excel VBA is used. Output formatted like R.
<lang vb>Private Function Test4DiscreteUniformDistribution(ObservationFrequencies() As Variant, Significance As Single) As Boolean
'Returns true if the observed frequencies pass the Pearson Chi-squared test at the required significance level.
Dim Total As Long, Ei As Long, i As Integer
Dim ChiSquared As Double, DegreesOfFreedom As Integer, p_value As Double
Debug.Print "[1] ""Data set:"" ";
For i = LBound(ObservationFrequencies) To UBound(ObservationFrequencies)
Total = Total + ObservationFrequencies(i)
Debug.Print ObservationFrequencies(i); " ";
Next i
DegreesOfFreedom = UBound(ObservationFrequencies) - LBound(ObservationFrequencies)
'This is exactly the number of different categories minus 1
Ei = Total / (DegreesOfFreedom + 1)
For i = LBound(ObservationFrequencies) To UBound(ObservationFrequencies)
ChiSquared = ChiSquared + (ObservationFrequencies(i) - Ei) ^ 2 / Ei
Next i
p_value = 1 - WorksheetFunction.ChiSq_Dist(ChiSquared, DegreesOfFreedom, True)
Debug.Print
Debug.Print " Chi-squared test for given frequencies"
Debug.Print "X-squared ="; ChiSquared; ", ";
Debug.Print "df ="; DegreesOfFreedom; ", ";
Debug.Print "p-value = "; Format(p_value, "0.0000")
Test4DiscreteUniformDistribution = p_value > Significance
End Function
Public Sub test()
Dim O() As Variant
O = [{199809,200665,199607,200270,199649}]
Debug.Print "[1] ""Uniform? "; Test4DiscreteUniformDistribution(O, 0.05); """"
O = [{522573,244456,139979,71531,21461}]
Debug.Print "[1] ""Uniform? "; Test4DiscreteUniformDistribution(O, 0.05); """"
End Sub</lang>
{{out}<pre>[1] "Data set:" 199809 200665 199607 200270 199649
Chi-squared test for given frequencies
X-squared = 4.14628 , df = 4 , p-value = 0.3866
[1] "Uniform? True"
[1] "Data set:" 522573 244456 139979 71531 21461
Chi-squared test for given frequencies
X-squared = 790063.27594 , df = 4 , p-value = 0.0000
[1] "Uniform? False"</pre>
=={{header|zkl}}==
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