tóng-àn:Normal Distribution PDF.svg

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Soat-bêng
English: A selection of Normal Distribution Probability Density Functions (PDFs). Both the mean, μ, and variance, σ², are varied. The key is given on the graph.
Ji̍t-kî
Chhut-chhù self-made, Mathematica, Inkscape
Chok-chiá Inductiveload
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R code

Plot[
 {
  PDF[NormalDistribution[1, Sqrt[2]], x],
  PDF[NormalDistribution[2, 1], x],
  PDF[NormalDistribution[3, Sqrt[3]], x],
    },
 {x, -5, 5},
 PlotRange -> All,
 Axes -> False]

Data

#			Normal Distribution PDF
#range
x=seq(-5,5,length=200)
#plot each curve
plot(x,dnorm(x,mean=0,sd=sqrt(.2)),type="l",lwd=2,col="blue",main='Normal Distribution PDF',xlim=c(-5,5),ylim=c(0,1),xlab='X',
ylab='φμ, σ²(X)')
curve(dnorm(x,mean=0,sd=1), add=TRUE,type="l",lwd=2,col="red")
curve(dnorm(x,mean=0,sd=sqrt(5)), add=TRUE,type="l",lwd=2,col="brown")
curve(dnorm(x,mean=-2,sd=sqrt(.5)), add=TRUE,type="l",lwd=2,col="green")

Text

#                    Normal Distribution
import numpy as np
import matplotlib.pyplot as plt 

def make_gauss(N, sig, mu):
    return lambda x: N/(sig * (2*np.pi)**.5) * np.e ** (-(x-mu)**2/(2 * sig**2))

def main():
    ax = plt.figure().add_subplot(1,1,1)
    x = np.arange(-5, 5, 0.01)
    s = np.sqrt([0.2, 1, 5, 0.5])
    m = [0, 0, 0, -2] 
    c = ['b','r','y','g']

    for sig, mu, color in zip(s, m, c): 
        gauss = make_gauss(1, sig, mu)(x)
        ax.plot(x, gauss, color, linewidth=2)

    plt.xlim(-5, 5)
    plt.ylim(0, 1)
    plt.legend(['0.2', '1.0', '5.0', '0.5'], loc='best')
    plt.show()

if __name__ == '__main__':
   main()

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Ji̍t-kî/Sî-kan細張圖寸尺Iōng-chiáChù-kái
hiān-chāi2016-nî 4-goe̍h 29-ji̍t (pài-gō·) 16:062016-nî 4-goe̍h 29-ji̍t (pài-gō·) 16:06版本的細圖720 × 460（63 KB）RayhemLighten background grid
2009-nî 9-goe̍h 22-ji̍t (pài-jī) 17:192009-nî 9-goe̍h 22-ji̍t (pài-jī) 17:19版本的細圖720 × 460（65 KB）StpashaTrying again, there seems to be a bug with previous upload…
2009-nî 9-goe̍h 22-ji̍t (pài-jī) 17:152009-nî 9-goe̍h 22-ji̍t (pài-jī) 17:15版本的細圖720 × 460（65 KB）StpashaCurves are more distinguishable; numbers correctly rendered in roman style instead of italic
2009-nî 6-goe̍h 27-ji̍t (pài-la̍k) 14:072009-nî 6-goe̍h 27-ji̍t (pài-la̍k) 14:07版本的細圖720 × 460（55 KB）Autiwafichier environ 2 fois moins gros. Purgé des définitions inutiles, et avec des plots optimisés au niveau du nombre de points.
2008-nî 9-goe̍h 5-ji̍t (pài-gō·) 18:222008-nî 9-goe̍h 5-ji̍t (pài-gō·) 18:22版本的細圖720 × 460（109 KB）PatríciaRfrom http://tools.wikimedia.pl/~beau/imgs/ (recovering lost file)
2008-nî 4-goe̍h 2-ji̍t (pài-saⁿ) 19:09Mò̤ sáuk-liŏk-dù（109 KB）Inductiveload{{Information |Description=A selection of Normal Distribution Probability Density Functions (PDFs). Both the mean, ''μ'', and variance, ''σ²'', are varied. The key is given on the graph. |Source=self-made, Mathematica, Inkscape |Date=02/04/2008 |Author

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