Given a population (maybe the population of all voters) and
given a subpopulation (maybe all voters who favor candidate A)
the goal of statistical sampling is to determine what percentage
of the population is in the subpopulation. This percentage
is known as the population proportion, denoted p.
When you take a sample you hope the percentage p^ (called the
sample proportion) of members of your sample which are in
the subpopulation will be close to the proportion p for
the whole population. Sometimes it will be but sometimes it won't be.
What you want to know is: how often is the sample proportion p^
close to the population proportion p? To answer this we
can look at the histogram of all possible samples with a
specified sample size. This webform draws the histogram
for all possible samples of size s taken from a population
of size N where the subpopulation of interest has size m.
The output is the histogram for the sampling distribution
for samples of size s taken from a population of size N
with a population proportion p = m/N. (So if you know your
population proportion p and population size N, then m = p*N.)
Requirements: 0 < N < 10^10, 0 < s <= N, 0 <= m <= N.