Detailed Explanation:
The correct answer is A. Each unit has an equal chance of being selected and the population is homogeneous.
Random sampling is most appropriate when the population being studied is reasonably uniform and every unit has an equal probability of selection. This helps ensure that the sample is unbiased and representative of the overall population.
Random sampling works best when:
the process output is relatively homogeneous,
there is no strong reason to divide the population into important subgroups,
and the evaluator wants an unbiased sample for general assessment.
This method supports fair representation because no unit is intentionally favored or excluded.
Why the other options are incorrect:
B. Specific subgroups within the population must be represented equally
This situation calls more for stratified sampling, not simple random sampling.
C. Selecting a predetermined percentage of units from each production shift
This is closer to stratified or quota-based sampling by subgroup, not pure random sampling.
D. Time constraints require selection of the most convenient items for evaluation
This is convenience sampling, which is generally less reliable and more prone to bias.
Quality Management Excellence reference basis:
This answer aligns with Quality Management Excellence principles of:
using appropriate data collection methods,
reducing sampling bias,
and selecting methods that match the structure of the population being evaluated.
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