899 words - 4 pages

Sampling

Carrying out a survey of every single potential consumer (known as

population) of a firm's product would be impractical, time-consuming

and costly. Businesses still, however, need to collect enough primary

data to have a clear idea of the views of consumers. This can be done

by taking a sample of the population. This sample group should be made

up of consumers that are representative of all potential buyers of the

product. There are a number of ways in which a sample can be chosen.

Random Sampling

This method gives each member of a group an equal chance of being

chosen. In other words, the sample is selected at random, rather like

picking numbers out of a hat. Today computers can be used to produce a

random list of numbers which are then used as the basis for selecting

a sample. Its main advantage is that bias cannot be introduced when

choosing the sample. However, it assumes that all members of the group

are the same (homogeneous), which is not always the case. A small

sample chosen in this way may not have the characteristics of the

population, so a very large sample would have to be taken to make sure

it was repetitive. It would be very costly and time consuming for

firms to draw up a list of the whole population and then contact and

interview them.

One method sometimes used to reduce the time taken to locate a random

sample is to choose every tenth or twentieth name on a list. This is

known as systematic sampling. It is, however, less random.

Stratified Random Sampling

This method of random sampling is often preferred by researchers as it

makes the sample more representative of the whole group. The sample is

divided in segments or strata based on previous knowledge about how

the population is divided up. So, if the business was interested in

how 'class' affected consumers' demand for a food product, it might

divide the population up into different class groups, such as working

class males, middle class females etc. A random sample could then be

chosen from each of these groups by making sure that they were the

same proportions of the sample in each category as in population as a

whole. So if the population had 10 per cent upper class males, so

would the sample.

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