"The bigger the sampling error, the bigger the confidence interval."

This statement was highlighted as true in an exam practice paper.

My confusion is:
1) Is CI and sampling error related to sample size
2) Is sampling error determined by (1-alpha)? If so, 95% CI has a larger sampling error compared to 99%, because it has 5% and 1% sampling error respectively hey? But doesn't this involve a decrease, not increase in CI?

Also, would be great if someone could explain the difference between a 95% and 99% confidence interval.


Omega Contributor

all you need to do is look up some of the formulas for confidence intervals to answer your questions.


CI = estimate +/- (alpha * SE)
depending on the distribution "n" is usually in the denominator of SE. So sample size is taken into account.

sampling error not determined by alpha, but a smaller alpha results in wider intervals given you want more confidence.