What is the purpose of confidence intervals in statistics?

Confidence intervals are used in statistics to provide a range of values that, with a certain level of confidence, is likely to contain the true value of an unknown parameter. This range is constructed based on sample data and reflects the inherent uncertainty when estimating population parameters.

In this context, defining a range with a pre-determined probability means that researchers can state, for instance, that they are 95% confident that the true population parameter lies within this interval. This concept is crucial because it allows statisticians to account for variability and provides a more comprehensive estimation than simply citing a single value.

Other options are related yet do not capture the primary function of confidence intervals. For instance, calculating the range of data values does not take into account the level of confidence associated with the estimate. Providing a single value ignores the uncertainty that confidence intervals are designed to address. Identifying the mode pertains to a specific measure of central tendency rather than encompassing a broader estimation framework of uncertainty.