# Training Educators to Design and Develop ODL Materials/Needs Analysis/SYSTEMATIC SAMPLING

Systematic sampling, sometimes called interval sampling, means that there is a gap, or interval, between each selection. This method is often used in industry, where an item is selected for testing from a production line (say, every fifteen minutes) to ensure that machines and equipment are working to specification.

Alternatively, the manufacturer might decide to select every 20th item on a production line to test for defects and quality. This technique requires the first item to be selected at random as a starting point for testing and, thereafter, every 20th item is chosen.

This technique could also be used when questioning people in a sample survey. A market researcher might select every 10th person who enters a particular store, after selecting a person at random as a starting point; or interview occupants of every 5th house in a street, after selecting a house at random as a starting point.

It may be that a researcher wants to select a fixed size sample. In this case, it is first necessary to know the whole population size from which the sample is being selected. The appropriate sampling interval, I, is then calculated by dividing population size, N, by required sample size, n, as follows:

I = N/n

If a systematic sample of 500 students were to be carried out in a university with an enrolled population of 10,000, the sampling interval would be:

I = N/n = 10,000/500 =20

Note: if I is not a whole number, then it is rounded to the nearest whole number.

All students would be assigned sequential numbers. The starting point would be chosen by selecting a random number between 1 and 20. If this number was 9, then the 9th student on the list of students would be selected along with every following 20th student. The sample of students would be those corresponding to student numbers 9, 29, 49, 69, ........ 9929, 9949, 9969 and 9989.

The advantage of systematic sampling is that it is simpler to select one random number and then every ‘Ith’ (e.g. 20th) member on the list, than to select as many random numbers as sample size. It also gives a good spread right across the population. A disadvantage is that you may need a list to start with, if you wish to know your sample size and calculate your sampling interval.