The confidence interval method for hypothesis testing (at the 95% level)relies on the fact that
A)95 percent of all sample statistics are correct.
B)the observed sample statistic is correct 95 percent of the time.
C)there is a 95 percent chance that the calculated confidence interval contains the true value of the unobserved population parameter.
D)95 percent of all confidence intervals that could be constructed contain the true value of the unobserved population parameter.

Question

Quizplus · Accepted Answer

The correct answer is D because it accurately describes the concept of a confidence interval. A 95% confidence interval means that if we were to take many samples and construct a confidence interval from each sample, 95% of those intervals would contain the true population parameter. This does not imply that any single interval has a 95% chance of containing the parameter, but rather describes the long-term behavior of confidence intervals constructed in this way.

The Confidence Interval Method for Hypothesis Testing (At the 95