What is one limitation of non-random sampling?

Non-random sampling is characterized by the selection of samples based on subjective judgment rather than random selection. One significant limitation of this approach is the potential for bias due to self-selection. When participants choose to be part of a study or survey, they may have distinct characteristics that are not representative of the larger population. This self-selection can lead to overrepresentation of certain groups or opinions, thus skewing the data and undermining the validity of any conclusions drawn from the findings.

For instance, if a survey is conducted online and only individuals who are particularly interested in the topic respond, the results may not reflect the views of those who are indifferent or unaware of the subject matter. This bias impacts the ability to generalize the findings to the entire population, as it does not provide a random cross-section of individuals. Consequently, while non-random sampling might be easier or more convenient, it tends to compromise the accuracy and reliability of the insights gained from the data.

Other options suggest characteristics that do not align with the inherent nature of non-random sampling, such as accurate representation, complete knowledge of the population, or guaranteed statistical significance, which are attributes associated with more rigorous sampling methods like random sampling.