Certified Professional in Learning and Performance (CPLP) 2025 – 400 Free Practice Questions to Pass the Exam

The process of drawing individuals randomly from a population is referred to as random sampling. This method ensures that every individual in the population has an equal chance of being selected, which helps to eliminate bias and makes the sample representative of the larger population. Random sampling is crucial in research and data collection as it enhances the validity of the results, allowing for generalization from the sample to the population.

Random selection is a term that is sometimes used interchangeably with random sampling, but in a more technical context, it often pertains to the initial step of identifying individuals for a sample from a broader population. Random assignment, on the other hand, refers to the process of assigning participants to different groups in a study after they have been selected, which is important for experimental design but not directly related to the selection process itself. Stratified random sampling involves dividing the population into subgroups and then randomly sampling from each subgroup, which is more specific than simple random sampling and not what the question describes.

Understanding the distinction among these terms can help clarify the importance of proper sampling techniques in research methodology.