Which statistical sampling method involves dividing the entire area into strata to capture variation in contamination?

• A. Simple random
• B. Hot spot sampling
• C. Stratified random
• D. A non-statistical

Answer: (C)

Dividing the study area into strata to capture variation in contamination is the idea behind stratified random sampling. By grouping locations into strata that are similar within each group but different between groups, you ensure that areas with distinct contamination levels are represented in the sample. Then sampling randomly within each stratum provides unbiased estimates for that subgroup, and combining those stratum estimates (weighted by the stratum’s size) gives a more precise overall estimate of contamination across the whole area. This approach reduces the sampling error that can come from spatial heterogeneity.

Simple random sampling across the whole area can miss important variation if contamination varies by location. Hot spot sampling focuses on known high-contamination areas, which can bias the overall estimate if the goal is to characterize variation throughout the area. A non-statistical approach lacks a probabilistic basis and cannot provide reliable measures of sampling error or represent the area comprehensively.