Final answer:
The term for the range of values related to a test set or question indicating the minimum and maximum for a parameter is called confidence intervals.
Step-by-step explanation:
The range of values related to a certain test set or question, which usually mark the minimum and maximum within which the true value of a parameter lies, is called confidence intervals. Confidence intervals are important in statistical analysis as they provide a range of values that are believed to contain the parameter of interest with a certain level of confidence. For example, if a 95% confidence interval for the mean of a dataset is calculated to be (10, 20), this means that we can be 95% confident that the true mean of the population from which the data were drawn lies between 10 and 20.
Confidence intervals consist of two parts: the point estimate, which is the single best estimate of the parameter based on the sample data, and the margin of error. The margin of error depends on the desired level of confidence and the standard error of the mean. Overall, confidence intervals are a fundamental concept in inferential statistics, allowing us to make probabilistic statements about population parameters based on sample data.