Chapter 12 Sampling Designs and Sampling Procedures

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Chapter 12Sampling Designs and Sampling
Procedures
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LEARNING OUTCOMES
After studying this chapter, you should be able to

• Define sample, population, population element,
  and census
  
• Explain reasons for taking a sample rather than a
  complete census
  
• Describe the process of identifying a target
  population and selecting a sampling frame
  
• Compare random sampling and systematic
  (nonsampling) errors
  
• Identify the types of nonprobability sampling,
  including their advantages and disadvantages

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LEARNING OUTCOMES (contd)
After studying this chapter, you should be able to

• Summarize the advantages and disadvantages of the
  various types of probability samples
  
• Discuss how to choose an appropriate sample
  design, as well as challenges for Internet
  sampling

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Sampling Terminology

• Sample
• A subset, or some part, of a larger population.
• Population (universe)
• Any complete group of entities that share some
  common set of characteristics.
  
• Population Element
• An individual member of a population.
• Census
• An investigation of all the individual elements
  that make up a population.

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Why Sample?

• Pragmatic Reasons
• Budget and time constraints
• Limited access to total population
• Accurate and Reliable Results
• Samples can yield reasonably accurate
  information
  
• Strong similarities in population elements makes
  sampling possible
  
• Sampling may be more accurate than a census
• Destruction of Test Units
• Sampling reduces the costs of research in finite
  populations.

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Practical Sampling Concepts

• Defining the Target Population
• What is the relevant population?
• Whom do we want to talk to?
• Population is operationally defined by specific
  and explicit tangible characteristics.
  
• The Sampling Frame (Working Population)
• A list of target population elements from which a
  sample may be drawn also called working
  population.

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Practical Sampling Concepts (contd)

• Sampling Frame Sources
• Sampling services (list brokers)
• Provide lists or databases of the names,
  addresses, phone numbers, and e-mail addresses of
  specific populations.
  
• Reverse directory
• A directory similar to a telephone directory
  except that listings are by city and street
  address or by phone number rather than
  alphabetical by last name.
• Sampling Frame Error
• Occurs when certain sample elements are not
  listed or are not accurately represented in a
  sampling frame.

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EXHIBIT 12.1Stages in the Selectionof a Sample
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EXHIBIT 12.2 Mailing List Directory Page
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Sampling Units

• Sampling Unit
• A single element or group of elements subject to
  selection in the sample.
  
• Primary Sampling Unit (PSU)
• A unit selected in the first stage of sampling.
• Secondary Sampling Unit
• A unit selected in the second stage of sampling.
• Tertiary Sampling Unit
• A unit selected in the third stage of sampling.

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Random Sampling and Nonsampling Errors

• Random Sampling Error
• The difference between the sample result and the
  result of a census conducted using identical
  procedures.
  
• A statistical fluctuation that occurs because of
  chance variations in the elements selected for a
  sample.
  
• Systematic Sampling Error
• Systematic (nonsampling) error results from
  nonsampling factors, primarily the nature of a
  studys design and the correctness of execution.
  
• It is not due to chance fluctuation.

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Random Sampling and Nonsampling Errors (contd)

• Less than Perfectly Representative Samples
• Random sampling errors and systematic errors
  associated with the sampling process may combine
  to yield a sample that is less than perfectly
  representative of the population.

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EXHIBIT 12.3 Errors Associated with Sampling
Source Adapted from Keith K. Cox and Ben M.
Enis, The Marketing Research Process (Pacific
Palisades, CA Goodyear, 1972) and Danny N.
Bellenger and Barnet A. Greenberg, Marketing
Research A Management Information Approach
(Homewood, IL Richard D. Irwin, 1978), pp.
154155.
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Probability versus Nonprobability Sampling

• Probability Sampling
• A sampling technique in which every member of the
  population has a known, nonzero probability of
  selection.
  
• Nonprobability Sampling
• A sampling technique in which units of the sample
  are selected on the basis of personal judgment or
  convenience the probability of any particular
  member of the population being chosen is unknown.

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Nonprobability Sampling

• Convenience Sampling
• Obtaining those people or units that are most
  conveniently available
  
• Judgment (Purposive) Sampling
• An experienced individual selects the sample
  based on personal judgment about some appropriate
  characteristic of the sample member.
  
• Quota Sampling
• Ensures that various subgroups of a population
  will be represented on pertinent characteristics
  to the exact extent that the investigator desires.

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Nonprobability Sampling (contd)

• Possible Sources Of Bias
• Respondents chosen because they were
• Similar to interviewer
• Easily found
• Willing to be interviewed
• Middle-class
• Needed to fill out the sample quota
• Advantages of Quota Sampling
• Speed of data collection
• Lower costs
• Convenience

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Nonprobability Sampling (contd)

• Snowball Sampling
• A sampling procedure in which initial respondents
  are selected by probability methods and
  additional respondents are obtained from
  information provided by the initial respondents.

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Probability Sampling

• Simple Random Sampling
• Assures each element in the population of an
  equal chance of being included in the sample.
  
• Systematic Sampling
• A starting point is selected by a random process
  and then every nth number on the list is
  selected.
  
• Stratified Sampling
• Simple random subsamples that are more or less
  equal on some characteristic are drawn from
  within each stratum of the population.

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Proportional versus Disproportional Sampling

• Proportional Stratified Sample
• The number of sampling units drawn from each
  stratum is in proportion to the population size
  of that stratum.
  
• Disproportional Stratified Sample
• The sample size for each stratum is allocated
  according to analytical considerations.

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Cluster Sampling

• Cluster Sampling
• An economically efficient sampling technique in
  which the primary sampling unit is not the
  individual element in the population but a large
  cluster of elements clusters are selected
  randomly.

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EXHIBIT 12.6 Examples of Clusters
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Multistage Area Sampling

• Multistage Area Sampling
• Involves using a combination of two or more
  probability sampling techniques.
  
• Typically, geographic areas are randomly selected
  in progressively smaller (lower-population)
  units.
  
• Researchers may take as many steps as necessary
  to achieve a representative sample.
  
• Progressively smaller geographic areas are chosen
  until a single housing unit is selected for
  interviewing.

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EXHIBIT 12.5Illustration of Multistage Area
Sampling
Source From Interviewers Manual, Revised
Edition (Ann Arbor, MI Survey Research Center,
Institute for Social Research, University of
Michigan, 1976), p. 36. Reprinted by permission.
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What Is the Appropriate Sample Design?
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EXHIBIT 12.6 Comparison of Sampling Techniques
Nonprobability Samples
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EXHIBIT 12.7 Comparison of Sampling Techniques
Probability Samples
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EXHIBIT 12.10 Comparison of Sampling Techniques
Probability Samples (contd)
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Internet Sampling is Unique

• Advantages
• Internet surveys can rapidly reach a large
  sample.
  
• Speed is both an advantage and a disadvantage
• Sample size requirements met almost
  instantaneously.
  
• Survey must be kept open long enough for all
  sample units to participate.
  
• Hard-to-reach subjects may participate
• Internet samples may be representative of a
  target population if the target population is
  visitors to a particular Web site
  
• Disadvantage
• Lack of computer ownership and Internet access
  among certain segments of the population

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Internet Sampling Sources
WebsiteVisitors
PanelSamples
Recruited Ad Hoc Samples
Opt-inLists
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Internet Sampling Is Unique (contd)

• Web Site Visitors
• Unrestricted samples are clearly convenience
  samples
  
• Randomly selecting visitors for a questionnaire
  request randomly "pops up"
  
• Samples may over-represent more frequent
  visitors
  
• Filters (e.g., cookies, passwords, and sign-ins)
  can identify unique visitors

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Internet Sampling Is Unique (contd)

• Panel Samples
• Typically yield a high response rate
• Members may be compensated for their time with a
  sweepstake or a small, cash incentive.
  
• Database on Members
• Demographic and other information from previous
  questionnaires
  
• Select quota samples based on
• Product ownership
• Lifestyle
• Other characteristics.

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Internet Sampling Is Unique (contd)

• Recruited Ad Hoc Samples
• Sample is recruited from databases of e-mail
  addresses compiled from customer/client lists,
  advertising banners, online sweepstakes, and
  registration forms.
• Opt-in Lists
• Subjects give permission to receive selected
  e-mail, such as questionnaires, from a company
  with an Internet presence.

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Key Terms and Concepts

• Sample
• Population (universe)
• Population element
• Census
• Sampling frame
• Reverse directory
• Sampling frame error
• Sampling unit
• Primary sampling unit (PSU)
• Secondary sampling unit
• Tertiary sampling unit
• Random sampling error

• Systematic (nonsampling) error
• Nonresponse error
• Probability sampling
• Nonprobability sampling
• Convenience sampling
• Judgment (purposive) sampling
• Quota sampling
• Snowball sampling
• Simple random sampling
• Systematic sampling
• Periodicity
• Stratified sampling

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Key Terms and Concepts (contd)

• Proportional stratified sample
• Disproportional stratified sample
• Cluster sampling
• Multistage area sampling
• Opt in