Image:Normal approximation to binomial.png

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Plot of the probability density function of a normal distribution approximating the probability mass function of a binomial distribution

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Note: "Norm(12, 3)" is a normal distribution with a mean of 12 and a standard deviation of 3. Its variance is 48 × 1/4 × 3/4 = 9.

gnuplot source under GPL:

# normal (Gaussian) distribution
_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) * 1.0/sd)

# binomial distribution
_ln_binom(x, n, p) =\
 lgamma(n+1) - lgamma(x+1) - lgamma(n-x+1) + x*log(p) + (n-x)*log(1-p)
dbinom(x, size, prob) = (x==int(x))? exp(_ln_binom(floor(x), size,  prob)) : 0
pbinom(x, size, prob) =\
 (x<0)? 0 : (x<size)? ibeta(size-floor(x), floor(x)+1, 1-prob) : 1

set terminal postscript enhanced color solid lw 2 "Times-Roman" 20
set output

set key 22,0.13

n = 48
p = 0.25
xmax = 25

set samples 50*xmax+1

plot [0:xmax] \
    dbinom(x, n, p) with impulses title "Binom(48, 0.25)", \
    dnorm(x, n*p, sqrt(n*p*(1-p))) linetype 3 title "Norm(12, 3)"

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