chapter ten copyright © 2006 john wiley & sons, inc. basic sampling issues
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Chapter TenChapter Ten
Copyright © 2006John Wiley & Sons, Inc.
Basic Sampling
Issues
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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 understand the differences between probability samples, and nonprobability samples.
5. To understand sampling implications of surveying over the Internet.
Learning Objectives
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To understand the concept of sampling.
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.
– The sample must be selected in a scientific manner to ensure that it is representative of the population from which it was selected
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• Population or Universe– The population or population of interest is the
total group of people from whom information is needed.
– Based on the characteristics of current or target customer
– Defining the population of interest is the first step in the sampling process
– Requires good logic and judgment
To understand the concept of sampling
The Concept of Sampling
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To understand the concept of sampling
• Sample versus Census – Census: Data about every member of the
population.– Sample: A subset of the population
The Concept of Sampling
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Step1.Define the
Population of Interest
Step 2. ChooseData Collection
Method
Step 3.Choose
Sampling Frame
Step 4. Select a
Sampling Method
Step 5. Determine
Sample Size
Step 6. Develop Operational Plan
Step 7.Execute
Operational Plan
Exhibit 10.1 Developing a Sample Plan
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To learn the steps in developing a sample plan.
Developing A Sampling Plan
• Step One: Defining the Population of Interest– Specify some combination of the following
• Geography characteristics
• Demographic characteristics
• Product or service use characteristics
• Awareness measures
– Create Screening questions to eliminate individuals who do not belong in the population of interest
– Also define the characteristics of those that should be excluded.
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To learn the steps in developing a sample plan.
• Step Two: Choose Data Collection Method– Data collection methods have implications for the
sampling process
• Step Three: Choosing Sampling Frame– A list of elements or members from which the
units to be sampled are selected– Identify the sampling frame—telephone book or
random-digit dialing.
Developing A Sampling Plan
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• 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
Developing A Sampling Plan
To learn the steps in developing a sample plan.
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Sampling methods
Probability samples
Systematic
Cluster
Stratified
Simple random
Nonprobability samples
Convenience
Judgment
Snowball
Quota
Exhibit 10-5 Classification of Sampling Methods
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• Probability Samples– A known, nonzero probability of selection– Simple random sample
• Every member of the population has a known and equal chance of being selected
• The laws of probability are in effect
• Allows sampling error to be calculated
To understand the differences between probability samples and nonprobability samples
Developing A Sampling Plan
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• Nonprobability Samples– Elements selected in a nonrandom manner.
• Nonrandomness—selected on the basis of convenience
• Purposeful nonrandomness—systematically excludes or overrepresents certain subsets of the population
To understand the differences between probability samples and nonprobability samples
Developing A Sampling Plan
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– Advantages Of Probability Samples• Information from a representative cross-section
• Sampling error can be computed
• Results are projectable to the total population.
– Disadvantages Of Probability Samples
• More expansive than nonprobabiity samples
• Take more time to design and execute.
Developing A Sampling Plan
To understand the differences between probability samples and nonprobability samples
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– Disadvantages of Nonprobability Samples• Sampling error cannot be computed
• Representativeness of the sample is not known
• Results cannot be projected to the population.
– Advantages of Nonprobability Samples• Cost less than probability
• Can be conducted more quickly
• Produces samples that are reasonably representative
.
Developing A Sampling Plan
To understand the differences between probability samples and nonprobability samples
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Steps In Developing A Sampling Plan
To learn the steps in developing a sample plan.
• Step Five: Determine Sample Size– Discussed more in depth in Chapter 11– Nonprobability Samples
• available budget• rules of thumb• number of subgroups to be analyzed in their determination of sample
size
– Probability Samples• Acceptable error • Levels of confidence
– The ability to make statistical inferences about population values
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Steps In Developing A Sampling Plan
To learn the steps in developing a sample plan
• Step Six: Develop of Operational Procedures for Selecting Sample Elements– Specify whether a probability or nonprobability
sample is being used– Procedures—detailed, clear, and unambiguous– Failure to do so can jeopardize the entire sampling
process• Step Seven: Execute the Sampling Plan
– Requires adequate checking to ensure that specified procedures are done.
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To understand the concepts of sampling error and
nonsampling error.
Sampling And Nonsampling
Errors
+- sns
+-X = X = sample mean
= true population mean
s = sampling error
ns = nonsampling error
• Sampling Error– The error that results when the same sample is not
perfectly representative of the population.
• Two types of sampling error:
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Probability Sampling Methods
To understand differences between probability samples and nonprobability samples
• Simple Random Sampling– Purest form of probability sampling– Known and equal probability is computed as
follows:Probability of selection =
• Using sampling frame the researcher can select a simple random sample
– Assign a number to each element of the population– Using a table of random numbers begin at some arbitrary
point and move up, down, or across
Sample SizePopulation Size
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• Systematic Sampling– Uses a fixed skip interval to draw elements from
a numbered population.
Skip Interval =
• Obtain a listing of the population and the entire population
• Determine a skip interval• Select names based on skip interval, using a random
starting point
Sample SizePopulation Size
Probability Sampling Methods
To understand differences between probability samples and nonprobability samples
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• 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.
– Subsets– Reasons not to use stratified samples
Probability Sampling Methods
To understand differences between probability samples and nonprobability samples
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• Three steps: 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.1. proportional allocation
2. disproportional or optimal allocation
3. Select separate simple random samples from each stratum
Probability Sampling Methods
To understand differences between probability samples and nonprobability samples
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• Cluster Samples– Two basic steps in cluster sampling
1. The population of interest is divided into mutually exclusive and exhaustive subsets.
2. A random sample of the subsets is selected.– One-stage cluster—all elements in subset selected– Two-stage cluster—elements selected in some probabilistic
manner from the selected subsets
– Not individual elements• Area sample—the clusters are units of geography• Main assumption—elements in cluster are heterogeneous
– Clusters samples—• generally less statistically efficient than other types of
probability samples
To understand differences between probability samples and nonprobability samples
Probability Sampling Methods
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Nonprobability Sampling Methods
• Convenience Samples– Easy to collect
• Judgment Samples– Based on judgmental selection criteria
• Quota Samples– Demographic characteristics in the same proportion as in
the population
• Snowball Samples– Additional respondents selected on referral from initial
respondents.
To understand differences between probability samples and nonprobability samples
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To understand sampling implications of surveying over the Internet.
Internet Sampling
• 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
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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– those who do not use the Internet have no chance
of being included
Internet SamplingTo understand sampling implications of surveying over the Internet.
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• The Concept of Sampling
• Developing a Sampling Plan
• Sampling and Nonsampling Errors
• Probability Sampling Methods
• Nonprobability Sampling Methods
• Internet Sampling
SUMMARY
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The End
Copyright © 2006 John Wiley & Sons, Inc.