Which sampling method ensures every member of a population has an equal chance of being selected?

The concept of ensuring that every member of a population has an equal chance of being selected is central to the principle of simple random sampling. This method utilizes randomization techniques to select participants from a larger population, meaning that each individual has the same probability of being chosen, regardless of their characteristics or circumstances.

In practical terms, simple random sampling can be achieved through methods such as using a random number generator or drawing names from a hat, which contributes to the representativeness of the sample and helps mitigate bias. This random selection process is fundamental in research as it enhances the validity of the findings by allowing researchers to generalize results to the broader population.

On the other hand, convenience sampling focuses on selecting individuals who are easiest to reach, which does not provide equal chances for everyone and can introduce significant bias. Systematic sampling involves selecting every nth individual from a list, which may not guarantee equal chances unless the list is arranged randomly. Stratified sampling divides the population into subgroups and then samples from each subgroup, which is useful for studying specific segments but does not ensure that every individual has an equal chance of being selected overall. Thus, simple random sampling stands out as the method that best fulfills the requirement of equal selection probability for all members of the population