Understanding Random vs. Representative Verification Sets For Predictive Modeling

Random sampling and representative sampling are distinct techniques. Random sampling assigns an equal chance for each population member to be chosen, possibly leading to underrepresented subgroups.

In contrast, representative sampling aims to mirror population traits, ensuring proportional subgroup inclusion. Illustrated with a water system study, representative sampling creates sets mimicking population characteristics, improving reliability. For utilities seeking accurate service line insights, predictive modeling via representative samples enhances unbiased estimates, cost-effective lead line identification, and streamlined public health protection.