Systematic sampling involves selecting a random starting point and then selecting every k-th element. Which option best describes this method?

• A. Systematic sampling
• B. Simple random sampling
• C. Cluster sampling
• D. Stratified sampling

Answer: (A)

Systematic sampling uses a random starting point in an ordered list and then selects every k-th element thereafter. The defining feature is that fixed interval between selections, which helps spread the sample across the population while keeping the process simple and efficient. The random start ensures each member has a chance to be included, while the regular skip creates a uniform pattern rather than choosing individual units entirely by chance.

This differs from simple random sampling, where selections are made purely at random without a set interval, so there’s no guaranteed spread across the list. It’s also different from cluster sampling, which groups units into clusters and samples whole clusters, and from stratified sampling, which divides the population into strata and samples within each one. Those methods don’t rely on a single, fixed interval across an ordered list.

A practical note: systematic sampling is convenient and can provide good coverage, but be aware of any underlying patterns in the list that might line up with the chosen interval and bias results.