Question at position 8 Dr. Sean is studying the effectiveness of a mobile mental health app across entire China. They randomly select 10 states, then within each state randomly select 5 hospitals, and finally sample 20 patients from each hospital who used the app. What sampling method is being used?b) Stratified random samplingd) Convenience samplinga) Simple random samplingc) Multistage sampling

Question

Question at position 8 Dr. Sean is studying the effectiveness of a mobile mental health app across entire China. They randomly select 10 states, then within each state randomly select 5 hospitals, and finally sample 20 patients from each hospital who used the app. What sampling method is being used?b) Stratified random samplingd) Convenience samplinga) Simple random samplingc) Multistage sampling

BlackTom AI · Accepted Answer

We first restate the scenario to ensure understanding: Dr. Sean samples in successive stages—10 states are randomly chosen, then within each state 5 hospitals are randomly chosen, and finally 20 patients from each hospital are sampled who used the app. This describes a hierarchical, multi-step process where sampling occurs at multiple levels, with random selection at each stage.

Option b) Stratified random sampling: This would involve dividing the population into non-overlapping strata and then taking a random sample from each stratum. In this scenario, states are not chosen as strata with proportional or equal samples, and hospitals are selected within states after states are chosen. The approach is not about sampling from predefined strata across the whole population but about sampling in stages, so this option is not correct.

Option d) Convenience sampling: This would mean selecting units that are easiest to reach or readily available, without randomization. Here, there is explicit random selection at each stage (states, then hospitals within states), so this is not convenience sampling.

Option a) Simple random sampling: This would require selecting individuals from the entire population with equal probability, typically via a single random draw. In the described design, individuals are not selected directly from the entire population in one step; instead, sampling occurs in multiple levels (states, then hospitals, then patients), which means it is not a simple random sample of all patients.

Option c) Multistage sampling: This matches the described method precisely. It involves sampling in successive stages, with random selection at each stage (states, then hospitals within those states, then patients within hospitals). This is a textbook example of multistage sampling (a form of cluster sampling conducted in stages).

In summary, the described process uses multiple levels of random sampling across different units, which aligns with multistage sampling. The other options do not capture the staged, hierarchical random selection structure present here.

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