In systematic sampling (also called systematic random sampling) every Nth member of population is selected to be included in the study. It is a probability sampling method. It has been stated that “with systematic sampling, every Kth item is selected to produce a sample of size n from a population size of N”. It requires an approximated frame for a priori but not the full list.
Systematic sampling method
According to wikipedia,
“Systematic sampling is a statistical method involving the selection of elements from an ordered sampling frame. The most common form it is an equiprobability method. In this approach, progression through the list is treated circularly, with a return to the top once the end of the list is passed.”
When to use
It is preferable to simple random sampling when there is a low risk of data manipulation. If such a risk is high when a researcher can manipulate the interval length to obtain desired results, a simple random sampling technique would be more appropriate. It is popular with researchers and analysts because of its simplicity. Researchers generally assume the results are representative of most normal populations unless a random characteristic disproportionately exists with every “nth” data sample. In other words, a population needs to exhibit a natural degree of randomness along the chosen metric. If the population has a type of standardized pattern, the risk of accidentally choosing very common cases is more apparent.
Advantages of systematic sampling
There are some important advantages are following,
· Operational convenience
· Field control
· Less non sampling error
· Reduced cost
· Greater efficiency
Disadvantages of systematic sampling
There are some disadvantages as following,
- Effect of periodicity
- Effect of trend
- Effect of ordering
- In Gallup poll.
- In quality control of a manufacturing company.
- In auditing of any sector (private or public sector)
- In market research for different goods or products.
- In crop estimation of agricultural field.
- In different health studies.