Which statement best defines a confidence interval?

Which statement best defines a confidence interval?

• A. A single estimate of a population parameter.
• B. The p-value of a test.
• C. The mean of a sample.
• D. Statistical range, with a given probability, that takes random error into account.

Answer: (D)

A confidence interval is a range around a sample estimate that reflects how much random sampling variation there is and gives a probability that the true population parameter lies within that range. It combines the point estimate (like the sample mean) with a margin of error derived from the data and the chosen confidence level. The stated probability (for example 95%) means that, if we repeated the study many times, about 95% of the constructed intervals would contain the actual parameter. It’s not a single estimate, and it’s not a p-value. It’s a way to express uncertainty due to sampling error. For example, an interval around the sample mean provides a plausible range where the true mean is likely to fall, given the data and method used.

A confidence interval is a range around a sample estimate that reflects how much random sampling variation there is and gives a probability that the true population parameter lies within that range. It combines the point estimate (like the sample mean) with a margin of error derived from the data and the chosen confidence level. The stated probability (for example 95%) means that, if we repeated the study many times, about 95% of the constructed intervals would contain the actual parameter. It’s not a single estimate, and it’s not a p-value. It’s a way to express uncertainty due to sampling error. For example, an interval around the sample mean provides a plausible range where the true mean is likely to fall, given the data and method used.