A researcher needs a sample of 500 items from a production line. The researcher includes all 50 items from each batch of items in a sample of 10 batches. Which sampling plan is described?
Cluster sampling is described in the sampling plan.
In this scenario, the researcher selects entire batches as clusters rather than individual items. By including all items from 10 batches, the researcher effectively employs cluster sampling, where clusters are natural groupings of the population.
Judgment sampling involves selecting items based on the researcher’s discretion or expertise, rather than a structured method. In this case, the researcher does not selectively choose batches based on personal judgment but instead includes all items from predefined batches, which does not align with the notion of judgment sampling.
Systematic sampling entails selecting items at regular intervals from a sampling frame, typically after a random start. This method would involve choosing every nth item from a list or sequence, which is not applicable here since the researcher is sampling complete batches rather than items at regular intervals.
Stratified sampling requires dividing the population into distinct subgroups or strata and then sampling from each stratum proportionally. Although batches can be considered strata, the method of including all items from selected batches does not reflect a stratified approach, which would involve random sampling within each stratum.
The sampling method described in the question is cluster sampling, where entire groups (batches) are included in the sample. This approach differs from judgment, systematic, and stratified sampling, which emphasize selection criteria based on individual items or specific proportions. Understanding these distinctions is crucial for implementing effective sampling strategies in research.
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