Loadingโฆ
Construct and interpret confidence intervals for a population mean using the t-distribution.
Learn step-by-step with practice exercises built right in.
What is a confidence interval and what does the confidence level represent?
A confidence interval is a range of plausible values for a population parameter, calculated from sample data. The confidence level (e.g., 95%) represents the long-run success rate: if we repeated our sampling procedure many times and computed a confidence interval each time, approximately 95% of those intervals would contain the true population mean . A 95% CI does NOT mean there is a 95% probability that is in this specific interval; rather, the interval either contains or it does not.
Avoid these 3 frequent errors
Review key concepts with our flashcard system
Explore more AP Statistics topics
where:
Common values (df = large, approximately normal):
For small samples:
Smaller df โ larger โ wider CI.
A random sample of 16 students has mean test score with sample SD s = 8. Find a 95% CI for the population mean.
Check conditions:
Calculate:
Interpretation: We are 95% confident the mean score is between 73.7 and 82.3.
Comparing two population means and :
where:
(Use technology to find df; approximately or more complex formula)
Free-response questions often ask you to construct a t-interval. Show all steps: state formula, check conditions, identify , s, n, df, and , calculate ME, and state the CI with interpretation. Partial credit is generous if you show correct understanding.
Given a sample of 25 students with mean , sample standard deviation , construct a 95% confidence interval for the population mean.
Conditions: Random sample, population approximately Normal or (assuming met). Formula: with . From t-table: . . CI: . We are 95% confident the population mean lies between 68.70 and 75.30.
Two researchers compute 90% confidence intervals for the same population mean. Researcher A uses , Researcher B uses . Whose interval is narrower? Explain why.
Researcher B's interval is narrower. The margin of error is . Since appears in the denominator, larger produces smaller and thus smaller . For A: . For B: . Researcher B's standard error is half as large, so the margin of error is smaller, producing a narrower interval. This demonstrates why larger sample sizes provide more precise estimatesโtighter confidence intervals.