Which of the following best describes the main difference between random and non-random sampling methods?

The core distinction between random and non-random sampling lies in the selection process. In random sampling, each member of the population has an equal chance of being chosen, which minimizes selection bias and improves the likelihood that the sample accurately reflects the population. Non-random sampling, on the other hand, often involves selecting individuals based on specific criteria, making it subjective and more prone to bias. This can affect the sample’s representativeness, although non-random sampling is sometimes used in cases where convenience or specific characteristics are necessary. Option A is incorrect because sample size is determined by study requirements, not the sampling method. Option B is incorrect as non-random sampling is applicable to both small and large datasets. Option D is incorrect because random sampling is typically more reliable in reducing selection bias. Option E is incorrect as random sampling is specifically designed to produce representative samples.