reset

go

verstecke Modell

μ_X = 1.1 (slider from -5 to 20, step 0.1)
σ_X = 1.2 (slider from 0.1 to 10, step 0.1)
σ_D = 0.4 (slider from 0.1 to 5, step 0.1)
n = 400 (slider from 1 to 400, step 1)
m = 0.5 (slider from -5 to 5, step 0.1)
b = 0.5 (slider from -5 to 5, step 0.1)
f(x) = (m * x) + b
Data_X = Sequence(RandomNormal[μ_X, σ_X], i, 1, n)
Data_D = Sequence(RandomNormal[0, σ_D], i, 1, n)
Data_Y: f(Data_X) + Data_D
Wolke: (Data_X, Data_Y)
S: (mean[Data_X], mean[Data_Y])
g = FitLineY(Wolke)
σ_Y: sqrt((m^(2) * σ_X^(2)) + σ_D^(2))
Bestimmtheitsmass_{Modell}: (m^(2) * σ_X^(2) / σ_Y^(2))
Korrelation_{Modell}: (m * σ_X / σ_Y)
Korrelation_{empirisch} = PMCC(Wolke)
Bestimmtheitsmaß_{empirisch}: Korrelation_{empirisch}^(2)
Text1 = LaTeX(Korrelation_{Modell}, true, true)
Text2 = LaTeX(Korrelation_{empirisch}, true, true)
Text3 = LaTeX(Bestimmtheitsmass_{Modell}, true, true)
Text4 = LaTeX(Bestimmtheitsmaß_{empirisch}, true, true)
l1: f(Data_X)
Residuen: (Data_X, Data_Y - g(Data_X))
Text5 = LaTeX(f, true, true)
i = 12
TeilWolke: (Take[Data_X, 1, i], Take[Data_Y, 1, i])
trend = FitLineY(TeilWolke)
M: (mean[x(TeilWolke)], mean[y(TeilWolke)])
Text7 = LaTeX(i, true, true)
verstecke = false
Text6 = LaTeX(trend, true, true)
TeilResiduen: (Take[Data_X, 1, i], Take[Data_Y, 1, i] - trend(Take[Data_X, 1, i]))
anz: 2