RESEARCH METHOD COHEN ok

110 SAMPLING
school governors, school secretaries, form teachers;
for pupils this might be friends, gang members,
parents, social workers and so on. It is critical
for researchers to consider not only whether
access is possible but also how access will be
undertaken – to whom does one have to go, both
formally and informally, to gain access to the target
group.
Not only might access be difficult but also
its corollary – release of information – might be
problematic. For example, a researcher might gain
access to a wealth of sensitive information and
appropriate people, but there might be a restriction
on the release of the data collection; in the field
of education in the UK reports have been known
to be suppressed, delayed or ‘doctored’. It is not
always enough to be able to ‘get to’ the sample, the
problem might be to ‘get the information out’ to
the wider public, particularly if it could be critical
of powerful people.
The sampling strategy to be used
There are two main methods of sampling (Cohen
and Holliday 1979; 1982; 1996; Schofield 1996).
The researcher must decide whether to opt for
aprobability(alsoknownasarandomsample)
or a non-probability sample (also known as a
purposive sample). The difference between them
is this: in a probability sample the chances of
members of the wider population being selected
for the sample are known, whereas in a nonprobability
sample the chances of members of the
wider population being selected for the sample
are unknown. In the former (probability sample)
every member of the wider population has an
equal chance of being included in the sample;
inclusion or exclusion from the sample is a matter
of chance and nothing else. In the latter (nonprobability
sample) some members of the wider
population definitely will be excluded and others
definitely included (i.e. every member of the wider
population does not have an equal chance of being
included in the sample). In this latter type the
researcher has deliberately – purposely – selected
aparticularsectionofthewiderpopulationto
include in or exclude from the sample.
Probability samples
Aprobabilitysample,becauseitdrawsrandomly
from the wider population, will be useful if the
researcher wishes to be able to make generalizations,
because it seeks representativeness of the
wider population. It also permits two-tailed tests
to be administered in statistical analysis of quantitative
data. Probability sampling is popular in
randomized controlled trials. On the other hand,
anon-probabilitysampledeliberatelyavoidsrepresenting
the wider population; it seeks only to
represent a particular group, a particular named
section of the wider population, such as a class
of students, a group of students who are taking
a particular examination, a group of teachers
(see http://www.routledge.com/textbooks/
9780415368780 – Chapter 4, file 4.6.ppt).
A probability sample will have less risk of
bias than a non-probability sample, whereas,
by contrast, a non-probability sample, being
unrepresentative of the whole population, may
demonstrate skewness or bias. (For this type of
sample a one-tailed test will be used in processing
statistical data.) This is not to say that the former is
bias free; there is still likely to be sampling error in a
probability sample (discussed below), a feature that
has to be acknowledged, for example opinion polls
usually declare their error factors, e.g. ±3percent.
There are several types of probability samples:
simple random samples; systematic samples; stratified
samples; cluster samples; stage samples, and
multi-phase samples. They all have a measure of
randomness built into them and therefore have a
degree of generalizability.
Simple random sampling
In simple random sampling, each member of the
population under study has an equal chance of
being selected and the probability of a member
of the population being selected is unaffected
by the selection of other members of
the population, i.e. each selection is entirely
independent of the next. The method involves
selecting at random from a list of the population
(a sampling frame) the required number of