Western Governors University (WGU) MGMT6010 C207 Data Driven Decision Making Practice Exam

The chosen answer is accurate because in sampling methods, each piece of the population can be selected only once in the context of sampling without replacement. This approach means that when an individual or item from the population is selected for the sample, it is not returned to the population for potential reselection. This methodology ensures that the sample is unique and that no individual or item can appear more than once in that particular sample, enhancing the integrity of the sample's diversity. In practice, this is useful when the goal is to have a distinct representation without duplicates, allowing for cleaner analysis and results that reflect true variability within the population. This contrasts distinctly with sampling with replacement, where selected individuals can be chosen again, leading to potential repeats within the sample. Random sampling and cluster sampling refer to different processes and do not inherently guarantee that each piece of the population is selected only once, especially since random sampling can involve replacing chosen units. Thus, sampling without replacement reliably facilitates the selection of unique samples from the population.