What two numbers are essential to quantify uncertainty?

The selection of interval (margin width) and confidence level is fundamental in quantifying uncertainty in statistical estimations. The margin of error, which is represented by the interval, indicates the range within which the true population parameter is expected to fall based on the sample data. This margin helps communicate the precision of the estimate.

The confidence level, on the other hand, reflects the degree of certainty associated with the estimate. For instance, a 95% confidence level suggests that if the same population were sampled multiple times, approximately 95% of the calculated confidence intervals would encompass the true population parameter. Together, these two measures provide a comprehensive understanding of uncertainty, allowing analysts to interpret the reliability of their findings.

Other options may include valuable statistical measures, but they do not specifically capture the dual aspects of uncertainty as effectively as the margin width and confidence level. For instance, while standard deviation and sample size provide insights into variation and reliability, they do not explicitly address the range and certainty of an estimate like the interval and confidence level do.