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Define cluster sampling by describing its two-stage selection procedure, and explain the unique advantage it possesses regarding the sampling frame compared to all other probability sampling methods.
Question: Define cluster sampling by describing its two-stage selection procedure, and explain the unique advantage it possesses regarding the sampling frame compared to all other probability sampling methods.
Sample answer: Cluster sampling is a probability sampling technique where researchers first randomly select larger groupings or 'clusters' of individuals—such as entire small towns or specific schools—and then randomly sample individuals from within those chosen clusters. Its unique advantage compared to other probability sampling methods is that it is the only approach that does not require a comprehensive sampling frame of the entire population.
Key points:
- Definition of cluster sampling as randomly selecting larger groupings (clusters) of individuals.
- Random sampling of individuals from within the chosen clusters.
- Explaining that it is uniquely the only probability sampling method that does not require a comprehensive sampling frame of the entire population.
Rubric: Grading Rubric: - 2 points: Accurately describes the two-stage selection procedure (randomly selecting larger clusters of individuals first, then randomly sampling individuals within those chosen clusters). - 2 points: Correctly identifies the unique advantage regarding the sampling frame (does not require a comprehensive sampling frame of the entire population). - 1 point: Mentions that it minimizes travel and logistical costs for face-to-face interviews.
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Research Methods in Psychology - 4th American Edition @ KPU
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