Which type of sampling is characterized by the use of a random number generator to select participants?

The correct answer is based on the definition of simple random sampling, which explicitly involves selecting participants in such a way that every individual in the population has an equal chance of being chosen. Using a random number generator ensures that the selection process is free from bias, allowing for a diverse and representative sample of the population.

In simple random sampling, each member of the population is assigned a unique number, and the random number generator selects participants at random without any pre-determined criteria or groupings. This method supports the assumption of independence among the samples, which is critical for many statistical analyses.

Other sampling methods, while useful, employ different techniques that do not solely rely on random selection across the entire population. Stratified sampling, for example, involves dividing the population into subgroups and then randomly sampling from these groups, which may introduce bias if the subgroups are not properly represented. Cluster sampling entails dividing the population into clusters and then randomly selecting entire clusters, rather than individuals, which may lead to variability based on the clusters selected. Systematic sampling selects participants based on a fixed interval from a randomly chosen starting point, which can also introduce a systematic bias if there is a pattern within the population's ordering.

Thus, the emphasis on random selection via a generator distinctly