Stratified Sampling

In a stratified sample the sampling frame is divided into non-overlapping groups or strata, e.g. geographical areas, age-groups, genders.  A sample is taken from each stratum, and when this sample is a simple random sample it is referred to as stratified random sampling.

Advantages

• Stratification will always achieve greater precision provided that the strata have been chosen so that members of the same stratum are as similar as possible in respect of the characteristic of interest.  The bigger the differences between the strata, the greater the gain in precision.  For example, if you were interested in Internet usage you might stratify by age, whereas if you were interested in smoking you might stratify by gender or social class.

• It is often administratively convenient to stratify a sample.  Interviewers can be specifically trained to deal with a particular age-group or ethnic group, or employees in a particular industry.  The results from each stratum may be of intrinsic interest and can be analysed separately.

• It ensures better coverage of the population than simple random sampling.

Disadvantages Difficulty in identifying appropriate strata. More complex to organise and analyse results.

Choice of Sample Size for each Stratum