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Research
Methods STA630
VU
Lesson
26
SAMPLE
AND SAMPLING TERMINOLOGY
A
sample
is
a subset, or some part, of a
larger whole. A larger whole
could be anything out
which
sample
is taken. That `whole' could
be a bucket of water, a bag of sugar, a
group of organizations, a
group
of students, a group of customers, or a
group mid-level managers in an
organization. A complete
group
of entities sharing some common set of
characteristics is population. In other
words, the totality
out
of which sample is drawn is
referred to as population.
Why
sample?
1.
Saves Cost, Labor, and
Time
Applied
research projects usually have budget and
time constraints. Since sample
can save financial
cost
as
well as time, therefore, to go
for sample study is
pragmatic.
Of
course, a researcher investigating a
population with an extremely
small number of population
elements
may elect to conduct a study on the total
population rather than a
sample because cost,
labor,
and
time constraints are relatively
insignificant.
Although
sample study cuts costs,
reduces labor requirements, and gathers
vital information quickly,
yet
there
could be other
reasons.
2.
Quality Management/supervision
Professional
fieldworkers are a scarce
commodity. In a large study rather
than employing less
qualified
staff
it may be advisable to do a sample
study and employ highly
qualified professional fieldworkers.
It
can
certainly affect the quality of the
study. At the same time it
may be easier to manage a
small group
and
produce quality information. Supervision,
record keeping, training, and so forth
would all be more
difficult
in a very large
study.
3.
Accurate and Reliable
Results
Another
major reason for sampling is
that samples, if properly
selected, are sufficiently
accurate in most
of
the cases. If the elements of a
population are quite
similar, only a small sample
is necessary to
accurately
portray the characteristics of interest.
Most of us have had blood samples
taken from the
finger,
the arm, or another part of body.
The assumption is that blood is
sufficiently similar through
out
the
body, the characteristics of the blood
can be determined on the basis of
sample.
When
the elements of population are
highly homogenous, samples are
highly representative of the
population.
Under these circumstances almost
any sample is as good as
another.
Samples
may be more accurate than
census. In a census study of
large population there is a
greater
likelihood
of non-sampling errors. In a survey
mistakes may occur that
are unrelated to the selection of
people
in the study. For example, a
response may be coded
incorrectly, or the keyboard operator
might
make
data entry error.
Interviewer mistakes, tabulation errors,
and other non-sampling errors
may
increase
during census because of the
increased volume of work. In
sample increased accuracy
is
possible
because the fieldwork and tabulation of
the data can be closely supervised
than would be
possible
in a census. In field survey, a
small, well trained, closely
supervised group may do a more
careful
and accurate job of collecting
information than a large
group of nonprofessional
interviewers
trying
to contact everyone.
4.
Sampling may be the Only
Way
Many
research projects, especially those in
quality control testing,
require the destruction of the
items
being
tested. If the manufacturer of firecrackers wished to
find out whether each
product met a
specific
production
standard, there would be no product
left after testing.
Similarly, consider the case of
electric
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Research
Methods STA630
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bulbs.
In testing the life of bulbs, if we were
to burn every bulb produced, there
would be none left to
sell.
This is destructive
sampling.
5.
Determine the Period of
Study
Interviewing
every element of a large population
without sampling requires lot of
time, may be a year
or
more.
In such a long period study,
even the seasonal variation may
influence the response pattern of
the
respondents.
For example, if the study
was aimed at measuring the level of
unemployment in a given
large
city, the unemployment rate produced by the
survey data would not
refer to the city as of the
beginning
of interviewing or as of the end. Researcher
may be forced to attribute the
unemployment to
some
hypothetical date, representing to the midpoint of the
study period. Hence it will be
difficult to
determine
the exact timing to which the data of the
study pertains.
Sampling
Terminology
There
are a number of technical terms
used in books on research and statistics
which need
explanation.
Some
of the important terms are:
Element
An
element is that unit about
which information is collected and
which provides the basis of
analysis.
Typically,
in survey research, elements
are people or certain types of
people. It is that unit
about which
information
is collected and that provides the
basis of analysis. It can be a person,
groups, families,
organizations,
corporations, communities, and so
forth.
Population
A
population is the theoretically specified
aggregation of study elements. It is
translating the abstract
concept
into workable concept. For
example, let us look at the
study of "college students."
Theoretically
who are the college
students? They might include
students registered in government
colleges
and/or private colleges, students of
intermediate classes and/or graduate
classes, students of
professional
colleges and/or non-professional colleges,
and many other variations.
In this way the pool
of
all available elements is
population.
Target
Population
Out
of the conceptual variations what exactly
the researcher wants to focus on.
This may also be
called
a
target population. Target
population is the complete group of
specific population elements
relevant to
the
research project. Target
population may also be
called survey
population i.e.
that aggregation of
elements
from which the survey sample
is actually selected.
At
the outset of the sampling process, it is
vitally important to carefully
define the target population
so
the
proper source from which the
data are to collected can be
identified. In our example of
`college
students"
finally we may decide to study the
college students from
government institutions located
in
Lahore,
who are studying social
sciences, who are aged 19
years of age, and hailing
from rural areas.
Sampling
The
process of using a small number of items
or parts of a larger population to
make conclusions about
the
whole population. It enables the
researchers to estimate unknown
characteristics of the population.
Sampling
Frame
In
actual practice the sample will be drawn
from a list of population
elements that is often
different from
the
target population that has
been defined. A sampling frame is the
list of elements from which
the
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Research
Methods STA630
VU
sample
may be drawn. A simple
example could be listing of
all college students meeting
the criteria of
target
population and who are
enrolled on the specified date.
A
sampling frame is also called the
working
population because
it provides the list that
can be worked
with
operationally. In our example,
such a list could be prepared
with help of the staff of
the selected
colleges.
Sampling
Frame Error
A
sampling frame error occurs
when certain sample elements
are excluded or when the
entire
population
is not accurately represented in the
sampling frame. The error
that occurs when
certain
sample
elements are not listed or
available and are not
represented in the sampling frame.
Sampling
Unit
A
sampling unit is that element or
set of elements considered for selection
in some stage of
sampling.
Sampling
may be done in single stage or in
multiple stages. In a simple,
single-stage sample, the
sampling
units are the same as the
elements. In more complex samples,
however, different levels
of
sampling
units may be employed. For
example, a researcher may
select a sample of Mohallahs
in
a
city,
and then select a sample of households
from the selected Mohallahs,
and finally may select
a
sample
of adults from the selected households.
The sampling units of these
three stages of sampling
are
respectively
Mohallah,
households, and adults, of which thee
last of these are the elements.
More
specifically,
the terms "primary sampling
units," "secondary sampling
units," and "final sampling
units"
would
be used to designate the successive
stages.
Observation
Unit
An
observation unit, or unit of
data collection, is an element or
aggregation of elements from
which the
information
is collected. Often the unit of analysis
and unit of observation are the
same the individual
person
but this need not be
the case. Thus the researcher
may interview heads of household
(the
observation
units) to collect information
about every member of the
household (the unit of
analysis).
Parameter
A
parameter is the summary description of a
given variable in a population.
The mean income of
all
families
in a city and thee age
distribution of the city's population
are parameters. An important
part
portion
of survey research involves the
estimation of population parameters on
the basis of sample
observation.
Statistic
A
statistic is the summary description of a
given variable in a survey
sample. Thus the mean income
computed
from the survey sample and
the age distribution of that
sample are statistics.
Sample statistics
are
used to make estimates of the population
parameters.
Sampling
Error
Probability
sampling methods seldom, if ever,
provide statistics exactly
equal to the parameters that
they
are
used to estimate. Probability
theory, however, permits us to estimate
the error to be expected for a
given
sample (more information to be sought
from professional in Statistics).
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