Consider estimating the proportion of WMU undergraduates whose
permanent residence is in Southwest Michigan. We may take a random sample
of, say, n=25
students and compute the sample proportion
.
If 9 out of the 25 students come from Southwest Michigan, then
.
Because of the ``luck of the draw'',
chances are the true proportion p is not exactly .36, but some number close
to .36. Can we find
an interval which we know contains p with say, at least
95% confidence?
Recall that the sample proportion
over different groups of 25
has a histogram that would look approximately normal with mean
p and SD
.
This means that there is
95% likelihood that
falls within
of p. Of course, this also means there is
95% likelihood that p falls within
of
.
In statistical shorthand,

The following table gives the
appropriate critical value z for typical values of
.
Example:
1. Suppose that 9 out of 25 randomly selected students live in Southwest Michigan.
a. Construct a 99% confidence interval for the true proportion of WMU students who live in Southwest Michigan .2. Suppose that 36 out of 100 randomly selected students live in Southwest Michigan.
b. Construct a 75% confidence interval for the true proportion of WMU students who live in Southwest Michigan .
a. Construct a 99% confidence interval for the true proportion of WMU students who live in Southwest Michigan .
b. Construct a 75% confidence interval for the true proportion of WMU students who live in Southwest Michigan .