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

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A general problem with random sampling is that you could, by chance, miss out a particular group in the sample. However, if you form the population into groups, and sample from each group, you can make sure the sample is representative.

In stratified sampling, the population is divided into groups called strata. A sample is then drawn from within these strata. Some examples of strata commonly used by the ABS are States, Age and Sex. Other strata may be religion, academic ability or marital status.

The committee of a school of 1,000 students wishes to assess any reaction to the re-introduction of Pastoral Care into the school timetable. To ensure a representative sample of students from all year levels, the committee uses the stratified sampling technique.

In this case the strata are the year levels. Within each strata the committee selects a sample. So, in a sample of 100 students, all year levels would be included. The students in the sample would be selected using simple random sampling or systematic sampling within each strata

Stratification is most useful when the stratifying variables are simple to work with, easy to observe and closely related to the topic of the survey.

An important aspect of stratification is that it can be used to select more of one group than another. You may do this if you feel that responses are more likely to vary in one group than another. So, if you know everyone in one group has much the same value, you only need a small sample to get information for that group; whereas in another group, the values may differ widely and a bigger sample is needed.

If you want to combine group level information to get an answer for the whole population, you have to take account of what proportion you selected from each group.