In systematic random sampling, what is typically defined first?

In systematic random sampling, the process begins by defining the natural ordering of the population from which the sample will be drawn. This ordering is essential because it dictates how you will select individuals or units from the population at regular intervals, which is the hallmark of systematic sampling. By establishing a natural order, researchers can systematically choose every nth member from a list or sequence, ensuring that the sample is spread evenly across the entire population.

Understanding the natural order allows researchers to avoid potential biases that might arise from arbitrary selection methods, as it creates a structured approach to sampling. This method can be particularly useful in situations where the population is too large to sample completely or where a simple random sample might be impractical.

While other aspects such as sample size and population characteristics are important components of the research design, they come into play after the natural ordering has been established. Defining subgroups could also be part of the overall sampling strategy, but in systematic random sampling, it is crucial to first understand how the population is organized to implement the sampling technique effectively.