Which probability sampling method allows every sampling unit to have an equal, nonzero chance of selection?

Simple random sampling (SRS) is the method where every sampling unit in the population has an equal, nonzero chance of being selected. This means that each individual or item in the population has the same chance of being included in the sample, which helps to eliminate bias and ensures that the sample is representative of the overall population.

In SRS, selection is typically carried out using random number generators or drawing lots, thereby guaranteeing that there is no inherent advantage to being selected or not. The primary benefit of this method is its simplicity and fairness, making it a foundational technique in statistical sampling.

On the other hand, systematic sampling involves selecting units based on a fixed interval, which does not ensure that all units have an equal chance of being chosen, especially if there is a pattern in the population that aligns with the selection interval. Cluster sampling selects entire groups or clusters rather than individuals, which can introduce bias if the clusters themselves are not representative. Probability sampling is a broader category that encompasses a variety of methods, including SRS, but the question specifically asks for the method that ensures each unit has an equal chance, which is distinctly fulfilled by simple random sampling.