Welcome: Powerpoint Templates
Welcome: Powerpoint Templates
Welcome: Powerpoint Templates
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A
PRESENTATION
ON
SAMPLING:
DESIGN & PROCEDURES
Presented To:
PowerpointProf. T. S. Shibin
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PRESENTED BY:
P for
POWERFULL
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SAMPLE or CENSUS
Population: Aggregate of all the elements that share
some common set of characteristics.
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SAMPLE Vs. CENSUS
PARAMETER SAMPLE CENSUS
Budget Small Large
Time available Short Long
Population size Large Small
Variance in characteristics Small Large
Cost of sampling errors Low High
Cost of nonsampling errors High Low
Nature of measurement Destructive Nondestructive
Attention to individual cases Yes No
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THE SAMPLING DESIGN PROCESS
Define the Target Population
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Define the Target Population
Target population is the collection of elements or objects that
possess the information sought by the researcher.
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Determine the Sampling Frame
Sampling frame is a representation of the elements of the
target population.
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Select a Sampling Technique
Bayesian Approach: Elements are selected sequentially and it
incorporates prior information about population parameters, costs and
probabilities associated with making wrong decisions.
Importance of the
Resource Decision
Nature of Research
Constraints
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Hardik
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Classification of
Sampling Methods
Sampling
methods
Probability
samples Nonprobability
samples
Simple
Cluster Judgement Quota
random
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Disadvantages of Nonprobability Samples
1. Sampling error cannot be computed
2. Representativeness of the sample is not known
3. Results cannot be projected to the population.
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Convenience Sampling
Convenience sampling attempts to obtain a sample of
convenient elements. Often, respondents are selected
because they happen to be in the right place at the right
time.
Use of students, and members of social
organizations.
“People on the street” interviews.
Olympic Convenience.
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A Graphical Illustration of
Convenience Sampling
A B C D E Group D happens to
1 6 11 16 21 assemble at a
convenient time and
2 7 12 17 22
place. So all the
3 8 13 18 23 elements in this Group
4 9 14 19 24 are selected. The
resulting sample
5 10 15 20 25 consists of elements 16,
17, 18, 19 and 20. Note,
no elements are
selected from group A,
B, C and E.
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Judgmental Sampling
Judgmental sampling is a form of convenience
sampling in which the population elements are selected
based on the judgment of the researcher.
Purchase engineers selected in industrial marketing
research.
Expert witnesses used in court.
Department store study in Metropolitan.
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A Graphical Illustration of
Judgemental Sampling
The researcher
A B C D E considers groups B, C
1 6 11 16 21 and E to be typical and
2 7 12 17 22 convenient. Within each
of these groups one or
3 8 13 18 23 two elements are
4 9 14 19 24 selected based on
5 10 15 20 25 typicality and
convenience. The
resulting sample
consists of elements 8,
10, 11, 13, and 24. Note,
no elements are selected
from groups A and D.
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Quota Sampling
Quota sampling may be viewed as two-stage restricted
judgmental sampling.
The first stage consists of developing control categories, or
quotas, of population elements.
In the second stage, sample elements are selected based on
convenience or judgment.
Population Sample
composition composition
Control
Characteristic Percentage Percentage Number
Sex
Male 48 48 480
Female 52 52 520
____ ____ ____
100 100 Powerpoint
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A Graphical Illustration of
Quota Sampling
A B C D E A quota of one
element from each
1 6 11 16 21
group, A to E, is
2 7 12 17 22 imposed. Within
3 8 13 18 23 each group, one
element is selected
4 9 14 19 24
based on judgment
5 10 15 20 25 or convenience. The
resulting sample
consists of elements
3, 6, 13, 20 and 22.
Note, one element is
selected from each
column or group.
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Snowball Sampling
In snowball sampling, an initial group of respondents is
selected, usually at random.
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A Graphical Illustration of
Snowball Sampling
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Kapil
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Simple Random Sampling
Each elements in population has a known and equal
probability of selection.
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Limitations:
Difficult to construct sampling frame.
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A Graphical Illustration of
Simple Random Sampling
A B C D E
Select five random
1 6 11 16 21 numbers from 1 to 25.
2 7 12 17 22 The resulting sample
consists of population
3 8 13 18 23 elements 3, 7, 9, 16, and
4 9 14 19 24 24. Note, there is no
element from Group C.
5 10 15 20 25
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Systematic Sampling
Sample is chosen by selecting a random starting point then
every ith element is selected.
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Stratified Sampling
Two step process in which population is partitioned in to sub
population or strata.
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The variables used in partition the population in to strata is
known as stratification variables.
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In proportionate stratified sampling, the size of the
sample drawn from each stratum is proportionate to the
relative size of that stratum in the total population.
A B C D E Randomly select a
1 6 11 16 21 number from 1 to 5
for each stratum, A to
2 7 12 17 22 E. The resulting
3 8 13 18 23 sample consists of
population elements
4 9 14 19 24 4, 7, 13, 19 and 21.
5 10 15 20 25 Note, one element
is selected from each
column.
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Navin
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Cluster Sampling
The target population is first divided into mutually exclusive
and collectively exhaustive subpopulations, or clusters.
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Types of Cluster Sampling
Cluster Sampling
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Elements within a cluster should be as heterogeneous as
possible, but clusters themselves should be as
homogeneous as possible. Ideally, each cluster should be
a small-scale representation of the population.
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A Graphical Illustration of
Cluster Sampling
A B C D E
1 6 11 16 21
2 7 12 17 22
3 8 13 18 23
4 9 14 19 24
5 10 15 20 25
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Other Probability
Sampling Techniques
Sequential Sampling: A probability sampling technique in
which the population elements are sampled sequentially,
data collection and analysis are done at each stage, and a
decision is made as to whether additional population
elements should be sampled.
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Choosing
Nonprobability Vs. Probability
Sampling
Conditions Favoring the Use of
Factors Non probability Probability
sampling sampling
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Nilesh
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A Classification of Internet Sampling
Internet Sampling
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Disadvantages of Internet Interviewing
Users of the internet are not representative of the
general population.
No comprehensive and reliable source of email
addresses exists.
EXAMPLE-
Customer evaluation
Online purchase evaluation
Student course evaluation
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Ethics in Marketing Research
Ethics of the Sponsor
Overt and covert purposes
Dishonesty in dealing with suppliers
Misuse of research information
Ethics of the Supplier
Violating client confidentiality
Improper execution of research
Abuse of Respondents
Falsifying answers
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THANK
YOU
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