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| Keywords: Normal Distribution PDF.svg 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 self-made Mathematica Inkscape 2008-04-02 Inductiveload other fields + Mathematica Code <source lang mathematica > Plot PDFNormalDistribution1 Sqrt2 x PDFNormalDistribution2 1 x PDFNormalDistribution3 Sqrt3 x x -5 5 PlotRange -> All Axes -> False </source> R Code <source lang r > 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 </source> Python Code <source lang python > 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 </source> Normal distribution Images with Mathematica source code Images with R source code Images with Python source code | ||||
