Which of the following best describes non-random sampling?

Non-random sampling involves selecting samples based on the researcher’s judgment or convenience rather than at random. This technique is commonly used when it is difficult or costly to select a random sample from a large population. Examples of non-random sampling include convenience sampling, where samples are chosen based on their availability, or judgment sampling, where the researcher selects a sample they believe to be representative. While non-random sampling is quicker and cheaper, it carries a higher risk of bias because it doesn’t give every member of the population an equal chance of selection. Why Other Options Are Wrong : A) Incorrect : This option describes a systematic sampling approach, which is a form of random sampling, not non-random. B) Incorrect : This is the definition of random sampling , where every individual has an equal chance of being selected. D) Incorrect : This describes systematic sampling , where every nth individual is selected. E) Incorrect : This refers to stratified random sampling , which is a random technique that selects samples from specific strata to ensure representation from each subgroup.