What is the key feature of systematic sampling?

The key feature of systematic sampling is its regular, ordered approach. It involves selecting samples at a uniform interval, or "systematically", from a larger population.

Here's a step-by-step explanation:

1. Define the Population: The first step in systematic sampling is to define the population from which you want to draw a sample. This could be anything from the number of people in a city, the number of students in a school, or the number of products in a warehouse.

2. Determine the Sampling Interval: The next step is to determine the sampling interval, which is the gap between the units you select for your sample. This is usually calculated by dividing the total population size by the desired sample size.

3. Select the First Unit: After determining the sampling interval, you randomly select the first unit from the population. This could be any unit within the first interval.

4. Apply the Sampling Interval: Once the first unit is selected, you then apply the sampling interval to select the subsequent units. For example, if your interval is 5, you would select every 5th unit after the first one you selected.

5. Continue Until Desired Sample Size is Reached: You continue this process until you have reached your desired sample size.

The key advantage of systematic sampling is its simplicity and efficiency, especially when dealing with large populations. However, it may not be as random as other sampling methods, and it may not be suitable if the population has a certain pattern or order that could bias the results.