Sampling Methods

Sampling Methods

A great deal of sociological research makes use of sampling. This is a

technique aiming to reduce the number of respondents in a piece of

research, whilst retaining - as accurately as possible - the

characteristics of the whole group.

The purpose of taking a sample is to investigate features of the

population in greater detail than could be done if the total

population was used, and to draw inferences about this population. In

addition, at the practical level, a sample is likely to be both

cheaper and quicker to investigate.

All sampling will involve error and sociologists have developed

sampling techniques in order to minimize this error. All methods of

sampling make use of a sampling frame.

Sampling frame

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A sampling frame is the list of members of the total population of

interest. From this list a sample to study can be drawn. For example,

such a list may be an electoral register, if information about those

with voting rights is sought, or the family practitioner committee

lists if a health survey is projected, or vehicle registration lists,

if car ownership or road transport is under study.

Types of sampling

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The random sample

For inferences about a population to be valid, the sample must be

truly representative, the only way to ensure this is to take a Random

sample. This involves using either random numbers or systematic

sampling. Random numbers are used to ensure that every individual in a

sampling frame has an equal chance of being selected as a member of

the sample. Systematic samplinginvolves randomly selecting the first

individual fro...

... middle of paper ...

...espondents reply out of a sample of 200, is this 45%

or 90% in favour of a particular action if 90 out of the 100 answer

yes?

Second, there will be choice involved at three levels in the sample

and all ca introduce bias. The choosing of the sample, the choosing of

questions, and the choosing of significant responses.

Finally, there is the judgment of interviewers, especially in quota

sampling.

Generally, sampling seeks to avoid the possibility of 'freaks'

occurring and the larger the sample, the less likelihood there is of

this happening. The greater the variety of characteristics in the

population being measured, the larger and more carefully designed the

sample needs to be. Ultimately, the operation of a sample survey comes

down to a running battle against sources of bias - a battle, which is

never won.