In my last post on quantitative and qualitative research, I describe the two different types of research conducted by firms (not forgetting primary and secondary research). With these types of research, the firms have to pick people to conduct the research on. This is known as sampling which is what this article will be on: Random sample, Quota sample, Stratified sample and Sample sizes.
Sampling is a way of ensuring that results are typical of the whole population, though only a sample of the population can be used.
Now with sampling, there are a few concerns in how to choose the 'right' people (sampling method) to carry out the research on and decide how large a number to use (sample size). The 'right' people being the type of people that can portray the views and opinions of the whole population. There are three main sampling methods:
This involves selecting respondents to ensure that everyone in the population has an equal chance of being picked. It sounds easy but its not. If an interviewer goes to a street corner one morning and asks passers-by for an interview, the resulting sample will be biased towards those who are not at work, who do not own a car and have time on their hands (the busy ones will refuse to be interviewed). As a result the sample will not be representative of the whole population. So achieving a truly random sample requires careful thought.
Research companies use the following methods:
- Pick names at random from the electoral register (e.g. every 50th name)
- Send an interviewer to the address given in the register
- If the person is out, visit up to twice more before giving up (this is to maximise the chances of catching those who lead busy social lives and are therefore rarely at home).
|An example of Quota sampling|