Research Sampling Methods: A Latimer Appleby Useful Guide
Research sampling is really about how we decide who we are going to talk to; it is an essential ingredient of market research – it is the part which lays down the selection of individuals who will be asked to supply the required information. Various methods can be used, but the method used should be the most effective and efficient for the collection of the required data.
The sample should be large enough to give statistically significance to the results obtained for the smallest group required for examination. Here a good “rule of thumb” is to work on the principle of a minimum of 100 respondents per sub group (or cell) that you want to analyse. For example, if you wanted to examine potential differences between six different age cohorts: 18-24 year olds; 25-34 year olds; 35-44 year olds; 45-54 year olds; 55-64 year olds; and those aged 65 or over; you would require a sample of 600 respondents.
We use two main forms of research sampling: random sampling and quota sampling.
Here every item in the universe (i.e. your chosen target group) to be surveyed is given a single and equal chance of being selected with every unit of the universe being included. As we might guess, there are strengths and weaknesses of random sampling.
No advance knowledge of any characteristic of the universe is required
Sampling biases can be pre-determined
Small minorities in the universe can be represented with the correct size of the total sample
The universe to be sampled must be unique
Mistakes are easy to make and maybe difficult to detect
Geographic spreads of the “pure” random sample can be extremely wide, with resultant contact difficulties and expense
A quota research sample is one in which the known proportions of major characteristics as they appear in the universe are deliberately made to appear e.g. housewives, certain age groups, people who have decorated their homes within the last 12 months.
No essential sub group can be accidentally omitted
Interviewer biases can be minimised by more exact instructions
Greater geographical concentration is possible
Sample errors are no greater than for a random sample
Detailed data about the characteristic proportions in the universe is necessary
Interviewer dishonesty in informant description is not always easy to detect
Minority sub groups may be over weighted
Which research sampling type should be used?
There is no right or wrong answer, but random sampling is principally used when you want a broad picture or have little knowledge about the area or target group being investigated.
Quota sampling is used when you know who you want to talk to and do not want to waste money talking to the wrong people.
Need help choosing the right research sampling method for you? Feel free to contact us.