McCormick+Schmitz Handbook for value chain research on - PACA

wise to supplement this material with the more detailed treatment provided in the relevant
chapter(s) of a good <strong>research</strong> methods textbook.
A.5.1 Sampling
The survey method relies on sampling. Questionnaires are usually administered to a
relatively small group, or sample, of a given population. This is because if you can learn
something about a large group by studying only a few of its members, then you have
saved time and money. What is necessary is to be able to generalise from the sample to
the population. Another way of putting this is that the sample must be representative of
the population. This means that the sample must be similar in important ways to the
population it represents. This, in turn, requires that you first define the population and
then ensure that your sample shares its major characteristics.
Let us suppose, <strong>for</strong> example, that you are trying to get in<strong>for</strong>mation on the work habits and
time spent by homeworkers in the garment producing region of your country. You would
need to be sure that the makeup of your sample in terms of age, education, ethnicity, years
of home working experience, and other critical variables is similar to that of the whole
population. If it is not, you could get skewed results. If, <strong>for</strong> instance, the homeworkers in
your sample are older or better educated than average, they may give different answers to
certain questions than would be obtained if the whole population could be surveyed. In
responding to questions about how caring <strong>for</strong> children affects their work, older
respondents may express different views simply because their children are older.
Getting a representative sample is, there<strong>for</strong>e, very important. The best and safest route to
a representative sample is some sort of probability (random) sampling technique. Such
techniques are based on the laws of probability: the chance of any element being in the
sample can be worked out mathematically. The most basic <strong>for</strong>m of probability sample is
the simple random sample, in which each element has an equal chance of being selected.
A sampling frame that lists all the population elements is necessary, since all must have a
chance of being included. If, as suggested above, you want a simple random sample of
homeworkers in the garment-producing district of your country, you would first have to
obtain or create a complete list. You next have to decide what size sample you want, and
then make your selection.
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