Which of the following is a key difference between random sampling and non-random sampling?

The primary difference between random sampling and non-random sampling is that random sampling gives every individual in the population an equal probability of being selected, which helps reduce bias and ensures that the sample is representative of the population. In contrast, non-random sampling, such as convenience or judgmental sampling, does not guarantee an equal chance for all members of the population to be selected. This can lead to bias, where certain individuals or groups are overrepresented or underrepresented. Random sampling is a core technique in probability-based sampling methods, making it more reliable for making generalizations about the population. The other options are incorrect because: • Option 2 (Size of the population) is incorrect. Both types of sampling can be used in small or large populations, though random sampling is generally more reliable in large populations. • Option 3 (Cost comparison) is not true. Random sampling can be more expensive due to its complexity in implementation. • Option 4 (Reliability) is incorrect as random sampling tends to produce more reliable results due to reduced bias. • Option 5 (Accuracy) is incorrect, as non-random sampling introduces a higher risk of bias, which can compromise the accuracy of the results.