Sampling Methods

Shantiram dahal
Survey Sampling Methods
Statistical method of obtaining representative data or observations from a group (lot, batch, population,
oruniverse).
Definitions of sampling on the Web:
• (statistics) the selection of a suitable sample for study

• sample distribution: items selected at random from a population and used to test hypotheses about the
population
• measurement at regular intervals of the amplitude of a varying waveform (in order to convert it to digital
form)
wordnetweb.princeton.edu/perl/webwn
• Sampling is that part of statistical practice concerned with the selection of an unbiased or random subset of
individual observations within a population of individuals intended to yield some knowledge about the
population of concern, especially for the purposes of making predictions based on ...
en.wikipedia.org/wiki/Sampling_(statistics)
• sample - a small part of something intended as representative of the whole
• take a sample of; "Try these new crackers"; "Sample the regional dishes"
• sample - all or part of a natural object that is collected and preserved as an example of its class
wordnetweb.princeton.edu/perl/webwn
• The Samples were a band formed in Boulder, Colorado in early 1987. The band's name came from the
members' early sustenance of food samples from the local King Soopers grocery store . ...
en.wikipedia.org/wiki/The_Samples
• Sample - In general, a sample is a limited quantity of something which is intended to be similar to and
represent a larger amount of that thing(s). The things could be countable objects such as individual items
available as units for sale, or a material not countable as individual items. ...
en.wikipedia.org/wiki/Sample_(material)
• SAMPLE history is an mnemonic acronym for first responders to remember key questions for patient
assessment. The history is usually taken along with vital signs. This is used for alert patients, but often
much of this information can also be obtained from the family of an unresponsive patient.
en.wikipedia.org/wiki/SAMPLE_(patient_interview)
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 selection technique.
After the required sample size has been calculated, every Nth 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.
Quota sampling is the nonprobability equivalent of stratified sampling. Like stratified sampling, the researcher first
identifies the stratums and their proportions as they are represented in the population. Then convenience or judgment
sampling is used to select the required number of subjects from each stratum. This differs from stratified sampling,
where the stratums are filled by random sampling.
Snowball sampling is a special nonprobability method used when the desired sample characteristic is rare. It may be
extremely difficult or cost prohibitive to locate respondents in these situations. Snowball sampling relies on referrals
from initial subjects to generate additional subjects. While this technique can dramatically lower search costs, it comes
at the expense of introducing bias because the technique itself reduces the likelihood that the sample will represent a
good cross section from the population.

Sampling Methods

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Shantiram dahal

Survey Sampling Methods

Definitions of sampling on the Web:

• (statistics) the selection of a suitable sample for study

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