Statistics 7.4-7.5: Large-Sample Confidence Interval for a Population Proportion (p)

Rule of thumb

if both np^ >= 15 and n(1-p^) >= 15, then it is safe to say that the sampling distribution of sample proportion (p^) is approximately normal

Required Conditions

1. A random sample is selected from the target population

2. The sample size n is large, that is, np^ >= 15 and n(1-p^) >= 15

Interpretation

In repeated sampling, we are 100(1-α)% confident that the true proportion (p) lies somewhere between….

Wilson’s adjustment for estimating p

if p is close to 0 or 1, this formula yields better results

Determining sample size

• to be within a certain sampling error (SE) of μ with a level of confidence equal to 100(1-α)%, we can solve for n

• round the calculated vale of n upwards to be sure you don’t have too small sample