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SAMPLING CONSIDERATIONS
RESEARCH CONCEPTS AND
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Sampling Concepts
Population: Population refers to any group of people or objects
that formthe subject of study in a particular survey and are
similar in one or more
ways.
Element: An element comprises a single member of the
population.
Sampling frame: Sampling frame comprises all the elements of
a
population with proper identification that is available to us
for selection at
any stage of sampling. Sample: It is a subset of the population.
It comprises only some elements
of the population.
Sampling unit:A sampling unit is a single member of the
sample.
Sampling: It is a process of selecting an adequate number of
elements
from the population so that the study of the sample will not
only help in
understanding the characteristics of the population but will
also enable usto generalize the results.
Census (or complete enumeration):An examination of each and
every
element of the population is called census or complete
enumeration.
RESEARCH CONCEPTS AND
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RESEARCH CONCEPTS AND
Advantages of Sample over
Census Sample saves time and cost.
A decision-maker may not have too much of time towait till all
the information is available.
There are situations where a sample is the onlyoption.
The study of a sample instead of completeenumeration may, at
times, produce more reliableresults.
A census is appropriate when the population size issmall.
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RESEARCH CONCEPTS AND
Sampling vs Non-Sampling Error Sampling error: This error arises
when a sample is not
representative of the population.
Non-sampling error: This error arises not because a sample isnot
a representative of the population but because of otherreasons.
Some of these reasons are listed below:
Plain lying by the respondent.
The error can arise while transferring the data from the
questionnaireto the spreadsheet on the computer.
There can be errors at the time of coding, tabulation and
computation.
Population of the study is not properly defined
Respondent may refuse to be part of the study.
There may be a sampling frame error.
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RESEARCH CONCEPTS AND
Sampling Design
Probability Sampling Design - Probability sampling designsare
used in conclusive research. In a probability samplingdesign, each
and every element of the population has aknown chance of being
selected in the sample.
Types of Probability Sampling Design Simple random sampling with
replacement
Simple random sampling without replacement
Systematic sampling
Stratified random sampling
Cluster sampling
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RESEARCH CONCEPTS AND
Sampling Design
Non-probability Sampling Designs - In case ofnon-probability
sampling design, the elements ofthe population do not have any
known chance ofbeing selected in the sample.
Types of Non-Probability Sampling Design
Convenience sampling
Judgmental sampling
Snowball sampling
Quota sampling
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Determination of Sample Size
The size of the population does not influence the size of
thesample
Methods of determining the sample size in practice:
Researchers may arbitrary decide the size of samplewithout
giving any explicit consideration to the accuracy ofthe sample
results or the cost of sampling.
The total budget for the field survey in a project proposal
isallocated.
Researchers may decide on the sample size based onwhat was done
by the other researchers in similar studies.
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Determination of Sample SizeConfidence interval approach for
determining the size of thesample
The following points are taken into account for determining
thesample size in this approach.
The variability of the population: Higher the variability
asmeasured by the population standard deviation, larger will be
thesize of the sample.
The confidence attached to the estimate: Higher the
confidencethe researcher wants for the estimate, larger will be
sample size.
The allowable error or margin of error: Greater the precision
theresearch seeks, larger would be the size of the sample.
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Determination of Sample Size
Sample size for estimating population mean -The formula for
determining sample size is given
as:
Where
n = Sample size
=
Population standard deviatione = Margin of error
Z = The value for the given confidence interval
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Determination of Sample Size
Sample size for estimating population proportion
1. When population proportion p is known
2. When population proportion p is not known
