File:Normal distribution cdf.svg
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Summary
editCumulative distribution function for the normal distribution
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Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.2 or any later version published by the Free Software Foundation; with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts. A copy of the license is included in the section entitled GNU Free Documentation License.http://www.gnu.org/copyleft/fdl.htmlGFDLGNU Free Documentation Licensetruetrue |
gnuplot source under GPL:
_ln_dnorm(x, m, s) = -1.5 * log(2*pi) - log(s) - 0.5*((x-m)*1.0/s)**2 dnorm(x, mean, sd) = exp(_ln_dnorm(x, mean, sd)) pnorm(x, mean, sd) = norm((x-mean) * 1.0/sd) set samples 1001 set terminal postscript enhanced color solid lw 2 "Times-Roman" 20 set output set xrange [-5:5] set xtics 1 set yrange [0:1] set ytics 0.1 #f(x,y,z) = dnorm(x, y, sqrt(z)) #use variance, not sd! #set key 3.8,0.94 f(x,y,z) = pnorm(x, y, sqrt(z)) set key 3.8,0.2 plot \ f(x, 0, 0.2) title "{/Symbol m} = 0, {/Symbol s}^2 = 0.2", \ f(x, 0, 1) title "{/Symbol m} = 0, {/Symbol s}^2 = 1.0", \ f(x, 0, 5) title "{/Symbol m} = 0, {/Symbol s}^2 = 5.0", \ f(x, -2, 0.5) title "{/Symbol m} = -2, {/Symbol s}^2 = 0.5"
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Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.2 or any later version published by the Free Software Foundation; with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts. A copy of the license is included in the section entitled GNU Free Documentation License.http://www.gnu.org/copyleft/fdl.htmlGFDLGNU Free Documentation Licensetruetrue |
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Date/Time | Thumbnail | Dimensions | User | Comment | |
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current | 15:42, 14 March 2006 | ![]() | 600 × 480 (39 KB) | Harp (talk | contribs) | Cumulative distribution function for the normal distribution {{GFDL}} gnuplot source under GPL: _ln_dnorm(x, m, s) = -0.5 * log(2*pi) - log(s) - 0.5*((x-m)*1.0/s)**2 dnorm(x, mean, sd) = exp(_ln_dnorm(x, mean, sd)) pnorm(x, mean, sd) = norm((x-mean) * |
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