Page 101 - DLIS401_METHODOLOGY_OF_RESEARCH_AND_STATISTICAL_TECHNIQUES

Methodology of Research and Statistical Techniques

Notes Sampling Methods

It is incumbent on the researcher to clearly define the target population. There are no strict
rules to follow, and the researcher must rely on logic and judgment. The population is defined
in keeping with the objectives of the study.
Sometimes, the entire population will be sufficiently small, and the researcher can include the
entire population in the study. This type of research is called a census study because data is
gathered on every member of the population.

Usually, the population is too large for the researcher to attempt to survey all of its members.
A small, but carefully chosen sample can be used to represent the population. The sample
reflects the characteristics of the population from which it is drawn.
Sampling methods are classified as either probability or nonprobability. In probability samples,
each member of the population has a known non-zero probability of being selected. Probability
methods include random sampling, systematic sampling, and stratified sampling. In nonprobability
sampling, members are selected from the population in some nonrandom manner. These include
convenience sampling, judgment sampling, quota sampling, and snowball sampling. The advantage
of probability sampling is that sampling error can be calculated. Sampling error is the degree
to which a sample might differ from the population. When inferring to the population, results
are reported plus or minus the sampling error. In nonprobability sampling, the degree to
which the sample differs from the population remains unknown.
Random sampling is the purest form of probability sampling. Each member of the population
has an equal and known chance of being selected. When there are very large populations, it
is often difficult or impossible to identify every member of the population, so the pool of
available subjects becomes biased.

Systematic sampling is often used instead of random sampling. It is also called an Nth name
th
selection technique. After the required sample size has been calculated, every N record is
selected from a list of population members. As long as the list does not contain any hidden
order, this sampling method is as good as the random sampling method. Its only advantage
over the random sampling technique is simplicity. Systematic sampling is frequently used to
select a specified number of records from a computer file.

Stratified sampling is commonly used probability method that is superior to random sampling
because it reduces sampling error. A stratum is a subset of the population that share at least
one common characteristic. Examples of stratums might be males and females, or managers
and non-managers. The researcher first identifies the relevant stratums and their actual representation
in the population. Random sampling is then used to select a sufficient number of subjects from
each stratum. “Sufficient” refers to a sample size large enough for us to be reasonably confident
that the stratum represents the population. Stratified sampling is often used when one or more
of the stratums in the population have a low incidence relative to the other stratums.
Convenience sampling is used in exploratory research where the researcher is interested in
getting an inexpensive approximation of the truth. As the name implies, the sample is selected
because they are convenient. This nonprobability method is often used during preliminary
research efforts to get a gross estimate of the results, without incurring the cost or time
required to select a random sample.
Judgment sampling is a common nonprobability method. The researcher selects the sample
based on judgment. This is usually and extension of convenience sampling. For example, a
researcher may decide to draw the entire sample from one “representative” city, even though
the population includes all cities. When using this method, the researcher must be confident
that the chosen sample is truly representative of the entire population.

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