CHAPTER twelve
Learning Objectives
Basic Sampling
Issues
Copyright © 2002
South-Western/Thomson Learning
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Learning Objectives
Learning Objectives
1. To understand the concept of sampling.
2. To learn the steps in developing a sampling
plan.
3. To understand the concepts of sampling error
and nonsampling error.
4. To distinguish between probability samples,
and nonprobability samples.
5. To understand sampling implications of
surveying over the Internet.
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Learning Objectives
The Concept of Sampling
To understand the
concept of sampling.
Sampling Defined:The process of obtaining information
from a subset of a larger group.
A market researcher takes the results from the sample to
make estimates of the larger group.
Sampling a small percentage of a population can result in
very accurate estimates.
It all depends on scientific selection.
E.g., 1,000 – 1,500 people polled to predict voting of tens of
millions
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Learning Objectives
Definition Of Important
Terms
To understand the
concept of sampling.
Population (or Universe)
The total group of people from whom we need to obtain
information.
Define the target market for the product or service in
question.
Sample versus Census
Census: Data about every member of the population.
Sample: A subset of the population
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Figure 12.1
Learning
Objectives
Steps in Developing
a Sample
Plan
Step 7.
Execute
Operational Plan
Step 6. Develop
Operational Plan
Step 5.
Determine
Sample Size
Step 2. Choose
Data Collection
Method
Step1.
Define the
Population of
Interest
Step 3.
Choose
Sampling Frame
(4)
Select a
Sampling Method
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Learning Objectives
Steps In Developing A
Sampling Plan
To learn the steps in
developing a sample plan.
Step One: Defining the Population of Interest
Specifying the characteristics from whom information is
needed.
Often specify in terms of geographic area,
demographics, usage, and awareness
Define the characteristics of those that should be
excluded.
Use screening or security questions
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Learning Objectives
Steps In Developing A
Sampling Plan
To learn the steps in
developing a sample plan.
Step Two: Choose Data Collection Method
Impacts for the sampling process.
E.g., telephone interviews, internet survey, etc.
Step Three: Choosing Sampling Frame
A list of elements or members from which we select units
to be sampled.
E.g., choose from phone book, or specify a procedure,
such a s questionnaire, that will produce the units to
be sampled.
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Learning Objectives
Steps In Developing A
Sampling Plan
To learn the steps in
developing a sample plan.
Name some possible sampling frames for:
1. Patrons of sushi bars
2. Smokers of high-priced cigars
3. Snowboarders
4. Owners of DVD players
5. People who have visited one or more countries in
Europe in the last year
6. People with allergies
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Learning Objectives
Steps In Developing A
Sampling Plan
To learn the steps in
developing a sample plan.
Step Four: Select a Sampling Method
The selection will depend on:
• The objectives of the study
• The financial resources available
• Time limitations
• The nature of the problem
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Learning Objectives
Steps In Developing A
Sampling Plan
To understand the steps in
developing a sample plan.
Probability Samples
A known, nonzero probability of selection
Nonprobability Samples
Elements selected in a nonrandom manner (e.g.,
based on convenience)
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Learning Objectives
Steps In Developing A
Sampling Plan
To distinguish between probability
samples and nonprobability samples.
Advantages of probability samples
• Obtain information from a representative crosssection
• Sampling error can be computed.
• The survey results are projectable to the total
population.
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Learning Objectives
Steps In Developing A
Sampling Plan
To distinguish between probability
samples and nonprobability samples.
Disadvantages of probability samples
• More expensive than nonprobability samples of
the same size.
• Probability samples take more time to design and
execute.
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Learning Objectives
Steps In Developing A
Sampling Plan
To distinguish between probability
samples and nonprobability samples.
Step Five: Determine Sample Size
For Nonprobability Samples:
• Available budget
• Rules of thumb
• Number of subgroups
For Probability Samples:
• Worry about acceptable error and levels of
confidence
• See Chapter 13.
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Learning Objectives
Steps In Developing A
Sampling Plan
To distinguish between probability
samples and nonprobability samples.
Step Six: Develop of Operational Procedures for
Selecting Sample Elements
Specify whether a probability or nonprobability sample is
being used
Procedures more critical for probability sample
Step Seven: Execution the Sampling Plan
The final step of the operational sampling plan
Include adequate checking of specified procedures.
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Figure 12.3
Learning Objectives
Classification of Sampling
Methods
Sampling
methods
Probability
samples
Systemati
c
Stratified
Cluster
Simple
random
Nonprobabilit
y samples
Convenienc
e
Judgment
Snowball
Quota
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Sampling And
Nonsampling Errors
Learning Objectives
To understand the concepts of
sampling error and nonsampling
error.
Sampling Error
The error that results when the same sample is not perfectly
representative of the population.
Two types of sampling error:
X=
 +- s +- ns
X = sample mean
 = true population mean
s = sampling error
ns = nonsampling (or measurement) error
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Sampling And
Nonsampling Errors
Learning Objectives
To understand the concepts of
sampling error and nonsampling
error.
Sampling Error
The error that results when the same sample is not perfectly
representative of the population.
• Administrative error: problems in the execution of
the sample
• Random error: due to chance and cannot be avoided
Nonsampling (Measurement) Error
Includes all other factors.
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Probability Sampling
Methods
Learning Objectives
To understand the differences in
probability and nonprobability
sampling methods.
Simple Random Sampling
The purest form of probability sample
Probability of Selection =
Sample Size
Population Size
E.g., if population size is 10,000, and sample size is 200,
probability of selection is 2%.
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Probability Sampling
Methods
Learning Objectives
To understand the differences in
probability and nonprobability
sampling methods.
Systematic Sampling
Uses a fixed skip interval to draw elements from a
numbered population.
Skip Interval =
Population Size
Sample Size
E.g., Pick every 500th name from the phone book.
Often simpler, less time-consuming, and less expensive
than simple random sampling.
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Probability Sampling
Methods
Learning Objectives
To understand the differences in
probability and nonprobability
sampling methods.
Stratified Samples
Probability samples that are distinguished by the following
steps:
1. The original population is divided into two or more
mutually exclusive and exhaustive subsets
2. Simple random samples of elements from the two or
more subsets are chosen independently from each
other.
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Probability Sampling
Methods
Learning Objectives
To understand the differences in
probability and nonprobability
sampling methods.
Three steps involved in implementing a properly stratified
sample:
1. Identify salient demographic or classification factors
correlated with the behavior of interest.
2. Determine what proportions of the population fall into
various sub subgroups under each stratum.
• proportional allocation
• disproportional or optimal allocation
3. Select separate simple random samples from each
stratum.
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Probability Sampling
Methods
Learning Objectives
To understand the differences in
probability and nonprobability
sampling methods.
Cluster Samples
Sampling units are selected in groups.
1. The population of interest is divided into mutually
exclusive and exhaustive subsets.
2. A random sample of the subsets is selected.
E.g., interview everyone in a particular neighborhood (to
reduce travel time and add to convenience)
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Nonprobability Sampling
Methods
Learning Objectives
To understand the differences in
probability and nonprobability
sampling methods.
Convenience Samples
Easy to collect
E.g., Ask your own employees, or rent a list of targeted
people
Judgment Samples
Based on judgmental selection criteria
E.g., go to a mall to conduct taste tests.
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Nonprobability Sampling
Methods
Learning Objectives
To understand the differences in
probability and nonprobability
sampling methods.
Quota Samples
Demographic characteristics in the same proportion as
in the population
E.g., asking males questions in a mall.
Snowball Samples
Additional respondents selected on referral from initial
respondents.
Good for “rare” populations, but leads to lesser sample
quality.
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Learning Objectives
Sampling Over the Internet
To understand sampling implications
of surveying over the Internet.
Advantages of Internet sampling:
• Target respondents can complete the survey at their
convenience
• Data collection is inexpensive
• The interview can be administered under software control
• The survey can be completed quickly
But…
• Not generally representative of entire population
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Learning Objectives
Sampling Over the Internet
To understand sampling implications
of surveying over the Internet.
Don’t Post Surveys in Public Areas
• Highly biased samples
• Vested interests quickly
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Learning Objectives
SUMMARY
• The Concept of Sampling
• Definition Of Important Terms
• Steps In Developing A Sampling Plan
• Sampling And Nonsampling Errors
• Probability Sampling Methods
• Nonprobability Sampling Methods
• Sampling Over the Internet
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Learning Objectives
The End
Copyright © 2002 South-Western/Thomson Learning
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