What type of sampling ensures that every member of the population has an equal chance of being selected?

A random sample is the method that guarantees every member of the population has an equal chance of being selected. This characteristic is essential for achieving unbiased representation of the population in research. When sampling is truly random, each individual has the same likelihood of being chosen, which helps to ensure that the sample reflects the diversity and characteristics of the entire population accurately.

In contrast, stratified sampling divides the population into distinct subgroups or strata and then samples from each stratum, which means that not all population members have an equal selection chance if they belong to a less-represented group. Systematic sampling follows a fixed, systematic approach to selecting participants (e.g., choosing every 5th person) which does not inherently provide equal chances for all individuals. Convenience sampling relies on selecting individuals who are easiest to reach, leading to potential bias since it does not account for the full diversity of the population.

Thus, a random sample is the most effective way to mitigate biases and ensure equal selection probability, making it a cornerstone technique in sociology and other social sciences.