What is defined as a range of values that estimates where a parameter is likely to lie?

The term that describes a range of values estimating where a parameter is likely to lie is the confidence interval. A confidence interval provides a method for quantifying the uncertainty around a statistical estimate, offering a range that reflects the degree of variability and potential error associated with that estimate. It typically conveys a specified level of confidence (often 95% or 99%) that the true parameter lies within that range based on the sample data.

In practical terms, if you are estimating a population mean based on a sample, the confidence interval allows you to present a range of values that not only gives an estimate but also offers insight into the reliability of that estimate.

For example, if a confidence interval for a mean measurement is calculated as 10 to 20, you can interpret this to mean that you are confident (at the chosen confidence level) that the true mean of the entire population lies somewhere between 10 and 20. This is critical in research and practice, as it aids in decision-making and understanding the magnitude of the uncertainties inherent in sampling.

Other concepts such as standard deviation, P-value, and statistical significance, while related to statistics, serve different purposes. Standard deviation measures the amount of variation or dispersion in a set of values, the P