What characterizes systematic sampling?

Systematic sampling is characterized by selecting elements from a larger population at regular intervals, which is defined by the fixed interval method. This approach involves taking a sample from a comprehensive list of the population, with an initial starting point typically chosen at random. Subsequent members are then selected at predetermined intervals, for example, every fifth or tenth individual on the list.

This method is efficient when a complete list of the population is available, as it simplifies the selection process and can lead to a representative sample without increasing the complexity of random sampling techniques. The fixed interval ensures that the sample maintains a consistent structure related to the population's sequence.

The other options describe characteristics of sampling methods but do not specifically capture the essence of systematic sampling. For instance, random selection is a broader term that could apply to various sampling techniques, while stratification involves dividing the population into subgroups based on specific characteristics before sampling, which is contrary to the method defined by fixed intervals in systematic sampling. Lastly, while having complete knowledge of the population is beneficial, it is not a defining characteristic unique to systematic sampling alone.