File:Normal Distribution PDF.svg

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Summary

Description
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.
Date
Source Own work (Original text: self-made, Mathematica, Inkscape)
Author Inductiveload
Permission
(Reusing this file)
Public domain I, the copyright holder of this work, release this work into the public domain. This applies worldwide.
In some countries this may not be legally possible; if so:
I grant anyone the right to use this work for any purpose, without any conditions, unless such conditions are required by law.
Category:Self-published work#Normal%20Distribution%20PDF.svgCategory:PD-self#Normal%20Distribution%20PDF.svg
SVG development
InfoField

Mathematica 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]

R Language Code

# Normal Distribution - Probability Density Function (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")

Python Code

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()
Category:Normal distribution Category:Images with Mathematica source code Category:Images with R source code Category:Images with Python source code
Category:Files allowed to be overwritten by everyone Category:Images with Mathematica source code Category:Images with Python source code Category:Images with R source code Category:Normal distribution Category:PD-self Category:Self-published work Category:Translation possible - SVG Category:Valid SVG created with Mathematica:Charts