Which term describes the percentage of time that intervals from repeated samples contain the true value?

The term that describes the percentage of time that intervals from repeated samples contain the true value is the confidence level. In statistics, the confidence level is a measure of how confident one can be that the true parameter (such as a population mean) falls within the estimated confidence interval derived from a sample. For example, a 95% confidence level suggests that if the sampling process were repeated numerous times, approximately 95% of the calculated confidence intervals would capture the true population parameter.

Understanding this term is essential in statistical analysis, especially when interpreting the reliability of sample estimates and the certainty associated with them. It plays a significant role in inferential statistics, where conclusions about a population are drawn based on sample data. While precision, repeatability, and tolerance are also important concepts in statistics and measurement, they do not specifically refer to the percentage of times that these intervals capture the true value as the confidence level does.