49. A researcher separates the area of a forest into 1,000 small regions. The researcher collects data on all of the trees in each of a sample of 20 small regions. Which sampling method is being used?
Answer: A
Cluster sampling is being used.
The researcher is employing cluster sampling by dividing the forest into 1,000 small regions and then collecting data from a sample of 20 of those regions. This method involves selecting entire groups or clusters rather than individual elements.
A) Cluster
This option is correct because cluster sampling involves dividing a population into groups (clusters) and then randomly selecting some of those groups to conduct a study. In this case, the 1,000 small regions represent clusters, and the researcher collects data from a sample of 20 of those regions.
B) Judgment
Judgment sampling is not applicable here as it relies on the researcher’s discretion to select specific samples based on their expertise or knowledge. In the scenario provided, the researcher is not selecting regions based on judgment but rather using a systematic approach to sample clusters.
C) Quota
Quota sampling involves selecting samples based on specific characteristics to meet a predetermined quota. Since the researcher is not sampling based on specific traits within the regions but rather randomly choosing whole regions, this option is incorrect.
D) Simple random
Simple random sampling means that every individual has an equal chance of being selected. In this case, the researcher is not selecting individual trees randomly but is instead sampling entire regions, making this option incorrect.
Conclusion
Cluster sampling is the definitive method being used in this scenario as the researcher collects data from entire regions rather than selecting individual trees randomly or based on judgment. All other options fail to accurately describe the sampling method since they do not involve the selection of entire groups or clusters.