In which sampling method does the researcher decide the sample size, express it as a ratio of the population, and then sample every kth person?

In which sampling method does the researcher decide the sample size, express it as a ratio of the population, and then sample every kth person?

• A. Systematic Random Sampling
• B. Simple Random Sampling
• C. Stratified Sampling
• D. Cluster Sampling

Answer: (A)

The method being described is systematic sampling. In systematic sampling you first decide how large the sample should be, which gives you a sampling interval by dividing the population size by the desired sample size (k = N/n). Then you choose a random starting point within the first interval and select every kth person thereafter. This approach creates a regular pattern across the population and ensures coverage over the entire list. This differs from simple random sampling, where you pick n individuals entirely at random without a fixed interval; from stratified sampling, which divides the population into subgroups and samples within each subgroup; and from cluster sampling, which involves selecting entire clusters and often surveying all individuals within chosen clusters rather than every kth person.

The method being described is systematic sampling. In systematic sampling you first decide how large the sample should be, which gives you a sampling interval by dividing the population size by the desired sample size (k = N/n). Then you choose a random starting point within the first interval and select every kth person thereafter. This approach creates a regular pattern across the population and ensures coverage over the entire list.

This differs from simple random sampling, where you pick n individuals entirely at random without a fixed interval; from stratified sampling, which divides the population into subgroups and samples within each subgroup; and from cluster sampling, which involves selecting entire clusters and often surveying all individuals within chosen clusters rather than every kth person.