

Research  sampling 


POPULATION
The group of people who are
the subject of a piece of research is known as the "population".
(Note that this does not necessarily refer to the entire population of a
country, or of a geographical locality  although it might.)




For example; in a piece of
research into Year 6 pupils' perceptions of secondary school, the
"population" would be ALL Year 6 pupils.



SUBSET
However, because it is often
not feasible to investigate the entire "population"  for reasons of
cost, time, accessibility, etc.  researchers are often obliged to
obtain data from a smaller group, known as a "subset" of the population.
Researchers (usually) seek to define the subset in such a way that the
data obtained will be representative of the total population. This
requires considerable care to ensure that the subset is not chosen in
such a way that respondents' bias will affect the results of the
research.




In our example, it would not
be appropriate to choose a sample that was taken entirely from Year 6
pupils from innercity primary schools. Their perceptions of
secondary school would most probably be based on the schools they know
(which are likely to be innercity schools) and would probably not be
representative of the whole population (of Year 6 pupils).



SAMPLE SIZE
It is not possible to say
with any certainty what size sample is appropriate. This will
depend on the size of the population and the purpose of the research.
If the researcher plans to subject the gathered data to some kind of
statistical analysis, the sample size needs to be large enough for that
analysis to be meaningful. Consequently, the researcher will need
to consider the number of variables that might affect the heterogeneity
(diversity) of the population.
When undertaking a survey,
researchers are likely to prefer a large sample, to ensure that the
effect of any variables within the sample are not exaggerated. In
qualitative research, however, the sample size is likely to be smaller 
because of the need to gather more indepth data.
Sample size is also likely
to be constrained by cost, time, personnel and resources.



REPRESENTATIVENESS
To ensure the validity of
the research, the researcher must do all they can to ensure that the
sample consulted represents the whole population in question.



ACCESS
Researchers need to bear in
mind not only the practicability of the chosen sample  but also whether
the sample can be accessed.




Gaining access to Year 6
pupils, for instance, could pose all kinds of difficulties. If it
is planned to carry out interviews, issues are raised regarding parental
permission, school cooperation, local education authority involvement,
etc. If it is intended to use questionnaires to gather data, not
only does the researcher need to consider the practical matters of
distribution and collection  but also the more fundamental issue of
whether the questions will be properly understood, interpreted and
answered by the target sample.



SAMPLING STRATEGIES
The two main methods of
sampling are PROBABILITY SAMPLING and NONPROBABILITY SAMPLING.



PROBABILITY SAMPLING
(also known as RANDOM
sampling)
The chances of members of
the wider population being selected for the sample are KNOWN.
Every member of the
population has an equal chance of being included in the sample.

NONPROBABILITY SAMPLING
(also known as PURPOSIVE
sampling)
The chances of members of
the wider population being selected for the sample are UNKNOWN.
Some members of the
population will definitely be included and others definitely excluded 
and hence every member of the population does NOT have an equal chance
of being included in the sample. The researcher will deliberately
select a particular section of the population for inclusion or exclusion
(based on a justifiable rationale).



PROBABILITY SAMPLING
Most useful if a researcher
wishes to make generalisations  because it seeks to be representative
of the whole population. There will be less risk of bias (whereas
a nonprobability sample, because it is not representative of the whole
population, may betray bias.)
There are various types of
probability samples:
Simple random sampling
A whole list of the
population is drawn up and members are selected at random until the
sample size is met. (One problem associated with this method is
that a complete list of the population is needed  and this may not be
available, depending on the nature of the research and the population
identified.)
Systematic sampling
Similar to simple random
sampling. A whole list of the population is drawn up and every
nth member of the list is chosen in order to achieve the sample
size. (For example, if a sample of 100 is required from a
population of 1000, every tenth member on the list is chosen  starting
from a random point.)
Stratified sampling
The population is divided up
into groups with similar characteristics (for example, males and
females) then members are selected randomly from within these groups at
the judgement of the researcher.
Cluster sampling
When the population is large
and widely dispersed (such as Year 6 pupils), obtaining a random sample
can pose administrative nightmares. The researcher may opt to
choose the sample from only a limited part of the population (say, from
schools within a specific geographical area).
Stage sampling
This is an extension of
cluster sampling. The researcher may select the sample in
stages  taking samples from samples. (For example, having limited
the choice to schools from a particular area, the researcher may then
randomly choose only a limited number of schools from those available 
and then only a limited number of pupils chosen at random from within
the selected schools.)
Multiphase sampling
Whereas in stage sampling
there is a single purpose throughout the sampling, in multiphase
sampling the purpose may change at each stage. (For example,
having limited the initial choice to schools from a particular area, the
researcher may then choose a limited number of schools within the area
based on whether they were innercity or suburban  and then choose a
limited number of pupils from within those schools in order to get a
range of pupils of differing abilities; based, for instance, on their
predicted KS2 SATs results.)



NONPROBABILITY SAMPLING
The usefulness of this
approach derives from the fact that the researcher is able to target a
specific group (in full knowledge that it does NOT represent the wider
population). This approach may be adequate if the researcher does
not intend to generalise their findings. It can also be
particularly useful if the researcher is trying to determine why a
specific section of the population appears not to be conforming to
expectations.
Nonprobability samples are
easier to set up, less complicated to administer and can be especially
useful for piloting a questionnaire prior to wider use amongst a wider
population.
There are various types of
nonprobability samples:
Convenience sampling
The researcher simply
chooses respondents from those closest to hand until the sample
size has been obtained. Also known as accidental or
opportunity sampling.
Quota sampling
Similar to stratified
sampling. The population is divided up into groups with
similar characteristics (for example, males and females) then members
are selected randomly from within these groups  but the numbers
selected are in proportion to their occurrence within the whole
population
Purposive sampling
Researchers hand pick the
members to be included in the sample on the basis of their typicality or
specific characteristics.
Dimensional sampling
This is a simplification of
quota sampling employed to reduce sample size. The
researcher identifies various factors of interest within the population
(for example, it may be important to include the responses of people of
different ages) then ensures that the sample includes respondents from
each of the groups thus identified.
Snowball sampling
The researcher identifies a
small number of respondents who possess a specific set of
characteristics of interest. The researcher then uses information
provided by these respondents to get in touch with others who also
possess the characteristics set. This can be particularly useful
for sampling a population where access is difficult  or who may not
readily be identified by more conventional means (for example, gang
members or drug addicts).



Cohen, L., Manion, L. &
Morrison, K. (2000) Research Methods in Education. London.
Routledge Farmer.



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