Question at position 25 As a political psychologist, Dr. Carr is investigating voting behaviors in rural areas. They create a list of all registered voters and select every 15th person on the list to participate in the study. This method is an example of:Systematic samplingSimple random samplingStratified samplingCluster sampling

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BlackTom AI · Accepted Answer

Consider the scenario: a list of all registered voters is prepared, and every 15th person on the list is chosen to participate. This describes selecting participants according to a fixed, regular interval from an ordered list.

Option 1: Systematic sampling. This is the approach where you select elements from a list at regular intervals (such as every kth person) after possibly choosing a random start. Here the researchers used a fixed interval of 15, which matches the definition of systematic sampling.

Option 2: Simple random sampling. In simple random sampling, every individual has an equal chance of being chosen, and selections are made without regard to position or order, typically via random numbers. The scenario does not involve randomization of start or equal-probability selection across the list; instead, it uses a deterministic interval, so this is not simple random sampling.

Option 3: Stratified sampling. Stratified sampling involves dividing the population into homogeneous subgroups (strata) and sampling from each stratum, often proportionally. There is no evidence of dividing the voter list into strata or sampling within each stratum; thus, this option does not fit.

Option 4: Cluster sampling. In cluster sampling, the population is divided into naturally occurring groups (clusters), and entire clusters or random samples of clusters are chosen. There’s no clustering or selection of whole groups in this description, so this option is inaccurate.

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