ꯐꯥꯏꯜ:IQ curve.svg

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ꯁꯟꯗꯣꯛꯅꯥ ꯇꯥꯛꯄꯥ Current IQ tests typically have standard scores such that the mean score is 100 with each standard deviation from the mean counting for 15 IQ points.[1] The plot shows, assuming that such scores have a normal distribution, the percentage of people getting a score versus the score itself, from 55 to 145 IQ, that is over a span of six standard deviations. Spans are represented with different colors for each standard deviation above or below the mean. The plot was created with the following gnuplot code:
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Gnuplot code

set terminal svg name 'IQ_curve' size 600,480 font ',10' rounded
set output 'IQ_curve.svg'

mu    = 100.0
sigma = 15.0
from  = 55
to    = 145

# Normal distribution:
# (continuos normalization approximation, good to ~10 digits in this case)
P(x) = exp(-(x - mu)**2 / (2 * sigma**2)) / (sqrt(2 * pi) * sigma) * 100
# By sigma intervals:
oddsi(x) = (int(abs(x - mu) / sigma) % 2) ^ (x < mu)
Pm(x) =               (x == mu)  ? P(x) : 1/0 # sample at mu
Po(x) = ( oddsi(x) && (x != mu)) ? P(x) : 1/0 # samples in odd sigma intervals
Pe(x) = (!oddsi(x) && (x != mu)) ? P(x) : 1/0 # samples in even sigma intervals

set key off
set border 3
set xlabel 'IQ'
set xtics 10 out nomirror
set mxtics 2
set ylabel 'Population, %'
set ytics 1 out nomirror
set mytics 2
set samples (to - from + 1)
set style function impulses
plot [x = from:to] \
 Pm(x) lw 2, \
 Po(x) lw 2, \
 Pe(x) lw 2
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ꯍꯧꯔꯛꯐꯛ ꯏꯁꯥ ꯏꯊꯟꯇꯒꯤ ꯑꯣꯏꯕꯥ ꯊꯕꯛ
ꯄꯨꯊꯣꯛꯂꯤꯕ ꯃꯤ Alessio Damato, Mikhail Ryazanov
  1. Kaufman, A.S. (꯲꯰꯰꯹) IQ Testing 101, New York (NY): Springer Publishing, pp. 104−109 ISBN: 978-0-8261-0629-2.

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ꯍꯧꯖꯤꯛꯀꯤ꯰꯴:꯴꯱, ꯲꯷ ꯅꯣꯚꯦꯝꯕꯔ ꯲꯰꯲꯰꯰꯴:꯴꯱, ꯲꯷ ꯅꯣꯚꯦꯝꯕꯔ ꯲꯰꯲꯰ꯒꯤ ꯃꯇꯨꯡ ꯏꯟꯅ ꯊꯝꯅꯦꯜ ꯚꯔꯖꯟ৬০০ × ৪৮০ (৯ KB)ParanajaReverted to version as of 21:27, 2 November 2012 (UTC)
꯰꯲:꯵꯷, ꯳ ꯅꯣꯚꯦꯝꯕꯔ ꯲꯰꯱꯲꯰꯲:꯵꯷, ꯳ ꯅꯣꯚꯦꯝꯕꯔ ꯲꯰꯱꯲ꯒꯤ ꯃꯇꯨꯡ ꯏꯟꯅ ꯊꯝꯅꯦꯜ ꯚꯔꯖꯟ৬০০ × ৪৮০ (৯ KB)Mikhail RyazanovIQ values are now integers; gnuplot-only approach
꯱꯴:꯵꯰, ꯶ ꯗꯤꯁꯦꯝꯕꯔ ꯲꯰꯰꯶꯱꯴:꯵꯰, ꯶ ꯗꯤꯁꯦꯝꯕꯔ ꯲꯰꯰꯶ꯒꯤ ꯃꯇꯨꯡ ꯏꯟꯅ ꯊꯝꯅꯦꯜ ꯚꯔꯖꯟ৬০০ × ৪৮০ (১২ KB)Alejo2083 {{Information |Description= The IQ test is made so that most of the people will score 100 and the distribution will have the shape of a Gaussian function, with a standard deviation of 15. The plot shows the percentage of people getting a score versus the

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