What is the main difference between simple random sampling and systematic sampling?

• A. A chance procedure vs a set interval
• B. One is probability-based, the other is nonprobability-based
• C. One always yields equal subgroup representation, the other does not
• D. One requires more resources

Answer: (A)

The main difference is in how selections are made. Simple random sampling uses a chance procedure where every unit in the sampling frame has an equal probability of being chosen, typically through randomization like a random number generator. Systematic sampling uses a fixed interval: after picking a random starting point, you select every kth item along the list (for example, every 20th item). This creates a regular, predictable pattern once the starting point is set.

Both methods are probability-based, but the mechanism differs—random draws for each selection versus a predetermined skip. Systematic sampling can be efficient and spread out across the list, but it can introduce bias if the list has a hidden pattern that matches the interval. The other statements aren’t the defining difference: both are probability-based, neither guarantees equal subgroup representation, and resource needs vary by context rather than by the fundamental method.