Chapter Eleven: Sampling: Design and Procedures
Chapter Eleven: Sampling: Design and Procedures
Chapter Eleven: Sampling: Design and Procedures
Sampling:
Design and Procedures
Sampling 11-1
Chapter Outline
1) Overview
2) Sample or Census
3) The Sampling Design Process
i. Define the Target Population
ii. Determine the Sampling Frame
iii. Select a Sampling Technique
iv. Determine the Sample Size
v. Execute the Sampling Process
Sampling 11-2
Chapter Outline
4) A Classification of Sampling Techniques
i. Nonprobability Sampling Techniques
a. Convenience Sampling
b. Judgmental Sampling
c. Quota Sampling
d. Snowball Sampling
ii. Probability Sampling Techniques
a. Simple Random Sampling
b. Systematic Sampling
c. Stratified Sampling
d. Cluster Sampling
e. Other Probability Sampling Techniques
Sampling 11-3
Chapter Outline
7. Internet Sampling
10. Summary
Sampling 11-4
Sample Vs. Census
Table 11.1
Conditions Favoring the Use of
Type of Study Sample Census
Sampling 11-5
The Sampling Design Process
Fig. 11.1
Sampling 11-6
Define the Target Population
The target population is the collection of elements or
objects that possess the information sought by the
researcher and about which inferences are to be made.
The target population should be defined in terms of
elements, sampling units, extent, and time.
Sampling 11-7
Define the Target Population
Important qualitative factors in determining the
sample size are:
Sampling 11-9
Classification of Sampling Techniques
Fig. 11.2
Sampling Techniques
Nonprobability Probability
Sampling Techniques Sampling Techniques
Sampling 11-10
Convenience Sampling
Sampling 11-11
A Graphical Illustration of
Convenience Sampling
Fig. 11.3
A B C D E
Group D happens to
assemble at a
1 6 11 16 21
convenient time and
place. So all the
2 7 12 17 22 elements in this
Group are selected.
The resulting sample
3 8 13 18 23 consists of elements
16, 17, 18, 19 and 20.
Note, no elements are
4 9 14 19 24
selected from group
A, B, C and E.
5 10 15 20 25
Sampling 11-12
Judgmental Sampling
test markets
purchase engineers selected in industrial
marketing research
bellwether precincts selected in voting behavior
research
expert witnesses used in court
Sampling 11-13
Graphical Illustration of Judgmental
Sampling
Fig. 11.3
A B C D E
The researcher
considers groups B, C
1 6 11 16 21 and E to be typical and
convenient. Within each
of these groups one or
2 7 12 17 22 two elements are
selected based on
typicality and
3 8 13 18 23 convenience. The
resulting sample
consists of elements 8,
4 9 14 19 24 10, 11, 13, and 24. Note,
no elements are selected
from groups A and D.
5 10 15 20 25
Sampling 11-14
Quota Sampling
Quota sampling may be viewed as two-stage restricted judgmental
sampling.
Population Sample
composition composition
Control
Characteristic Percentage Percentage Number
Gender
Male 48 48 480
Female 52 52 520
____ ____ ____
100 100 1000
Sampling 11-15
A Graphical Illustration of
Quota Sampling
Fig. 11.3
A B C D E
A quota of one
element from each
1 6 11 16 21 group, A to E, is
imposed. Within each
group, one element is
2 7 12 17 22 selected based on
judgment or
convenience. The
3 8 13 18 23 resulting sample
consists of elements
3, 6, 13, 20 and 22.
4 9 14 19 24 Note, one element is
selected from each
column or group.
5 10 15 20 25
Sampling 11-16
Snowball Sampling
Sampling 11-17
A Graphical Illustration of
Snowball Sampling
Random
Selection Referrals
A B C D E
Elements 2 and 9 are
selected randomly
1 6 11 16 21
from groups A and B.
Element 2 refers
elements 12 and 13.
2 7 12 17 22
Element 9 refers
element 18. The
3 8 13 18 23 resulting sample
consists of elements
2, 9, 12, 13, and 18.
4 9 14 19 24
Note, there are no
element from group E.
5 10 15 20 25
Sampling 11-18
Simple Random Sampling
Sampling 11-19
A Graphical Illustration of
Simple Random Sampling
Fig. 11.4
A B C D E
Select five
1 6 11 16 21 random numbers
from 1 to 25. The
2
resulting sample
7 12 17 22
consists of
population
3 8 13 18 23 elements 3, 7, 9,
16, and 24. Note,
4
there is no
9 14 19 24
element from
Group C.
5 10 15 20 25
Sampling 11-20
Systematic Sampling
The sample is chosen by selecting a random starting
point and then picking every ith element in
succession from the sampling frame.
Sampling 11-21
Systematic Sampling
Sampling 11-22
A Graphical Illustration of
Systematic Sampling
Fig. 11.4
A B C D E
Select a random
number between 1 to
1 6 11 16 21
5, say 2.
The resulting sample
2 7 12 17 22 consists of
population 2,
(2+5=) 7, (2+5x2=) 12,
3 8 13 18 23
(2+5x3=)17, and
(2+5x4=) 22. Note, all
4 9 14 19 24 the elements are
selected from a
single row.
5 10 15 20 25
Sampling 11-23
Stratified Sampling
A two-step process in which the population is
partitioned into subpopulations, or strata.
Sampling 11-25
Stratified Sampling
Sampling 11-26
A Graphical Illustration of
Stratified Sampling
Fig. 11.4
A B C D E
Randomly select a
1 6 11 16 21
number from 1 to 5
for each stratum, A to
E. The resulting
2 7 12 17 22
sample consists of
population elements
3 8 13 18 23 4, 7, 13, 19 and 21.
Note, one element
is selected from each
4 9 14 19 24
column.
5 10 15 20 25
Sampling 11-27
Cluster Sampling
Sampling 11-28
Cluster Sampling
Sampling 11-29
A Graphical Illustration of
Cluster Sampling (2-Stage)
Fig. 11.4
A B C D E
Randomly select 3
clusters, B, D and E.
1 6 11 16 21
Within each cluster,
randomly select one
2 7 12 17 22 or two elements. The
resulting sample
consists of
3 8 13 18 23 population elements
7, 18, 20, 21, and 23.
4 9 14 19 24 Note, no elements
are selected from
clusters A and C.
5 10 15 20 25
Sampling 11-30
Types of Cluster Sampling
Fig 11.5
Cluster Sampling
Sampling 11-31
Strengths and Weaknesses of
Basic Sampling Techniques
Table 11.3
Technique Strengths Weaknesses
Nonprobability Sampling Least expensive, least Selection bias, sample not
Convenience sampling time-consuming, most representative, not recommended for
convenient descriptive or causal research
Judgmental sampling Low cost, convenient, Does not allow generalization,
not time-consuming subjective
Quota sampling Sample can be controlled Selection bias, no assurance of
for certain characteristics representativeness
Snowball sampling Can estimate rare Time-consuming
characteristics
Sampling 11-32
Choosing Nonprobability Vs.
Probability Sampling
Table 11.4
Conditions Favoring the Use of
Factors Nonprobability Probability
sampling sampling
Sampling 11-33
Tennis' Systematic Sampling
Returns a Smash
Tennis magazine conducted a mail survey of its subscribers to
gain a better understanding of its market. Systematic sampling
was employed to select a sample of 1,472 subscribers from the
publication's domestic circulation list. If we assume that the
subscriber list had 1,472,000 names, the sampling interval
would be 1,000 (1,472,000/1,472). A number from 1 to 1,000
was drawn at random. Beginning with that number, every
1,000th subscriber was selected.
Sampling 11-34