This document discusses sampling design for research. It explains that sampling design refers to the method used to collect data from a subset of a population. A proper sampling design starts with a sample that is representative of the population. There are two main types of sampling: census, which investigates all individuals in a population, and sampling, which uses a small number from the larger population due to constraints. The document outlines key concepts in sampling design including the target population, study population, sampling frame, probability and non-probability sampling methods, and factors to consider for an appropriate sample size and design.

1. Sampling Design
R.VASANTHAGOPAL PhD
University of Kerala

2. 26 April 2020 R.Vasanthagopal PhD 2
Research
 Research-
 organized set of activities
 to find practical solution
 for a realistic problem
 supported by data

3. Research Process
 Formulating the research problem
 Survey and review of literature
 Asking research questions and developing hypothesis
 Deciding on the research design
 Sampling design
 Collecting data
 Analysis and interpretation of data
 Testing the hypotheses
 Findings, conclusion and suggestions
 Report writing
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4. Sampling Design…..
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Design of a sample refers to
the method used to collect the
data
A proper sampling design
must start with a sample
which is representative of the
population

5. Census Vs. Sampling
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Investigation of
all individual
elements
Using a small
number of items
of larger
population
Impracticable to
survey the entire
population
Budget
constraints
Time constraints
Immediate need
of results

6. Target Population, Study Population and Sample
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Sampling frame: The list from which the
potential respondents are drawn viz. list
of employees

7. Sampling Scheme/Methods/Techniques
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All units in
the
population
have an
equal
probability of
being chosen
Sample
selection
not based
on the
rationale of
probability
theory

8. Probability Vs. Non-probability Sampling
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9. What is Appropriate Sample Design?
 Degree of accuracy
 Resources
 Time
 Need for statistical analysis
 Representative of the population
 Appropriately sized (the larger the better)
 Random (selections occur by chance)
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10. Determination of Sample Size
A survey estimated that 20% of all
Indians aged 21 to 35 drove under
the influence of alcohol. A similar
survey is planned for Kerala. They
want a 95% confidence interval to
have a margin of error of 0.04.
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n=.20(1-.20)1.96x1.96/.04x.04
=384.2
Note: z is the z-score, e.g. 1.645 for a 90%
confidence interval,1.96 for a 95% confidence
interval, 2.58 for a 99% confidence interval
Note: Typical surveys have margins of error ranging from
less than 1% to something of the order of 4% - we can
choose any margin of error we like but need to specify it.
Sample size formula
n=N/1+Ne2
Solvin’s(1960) Formula(When population is known.
Where e=Margin of error