1. BUSINESS MARKET RESEARCH
ZIKMUND BABIN
CARR GRIFFIN
BUSINESS MARKET RESEARCH
EIGHTH EDITION

2. LEARNING OUTCOMES After studying this chapter, you should be able to
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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3. LEARNING OUTCOMES (cont’d)
After studying this chapter, you should
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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4. Sampling Terminology Sample Population (universe) Population Element
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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5. Why Sample? Pragmatic Reasons Accurate and Reliable Results
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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6. EXHIBIT 16.1 A Photographic Example of How Sampling Works
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7. EXHIBIT 16.2 Stages in the Selection of a Sample
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8. 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
A list of elements from which a sample may be drawn; also called working population.
Sampling Frame Error
Occurs when certain sample elements are not listed or are not accurately represented in a sampling frame.
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9. EXHIBIT 16.3 Mailing List Directory Page
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10. Practical Sampling Concepts (cont’d)
Sampling services (list brokers)
Provide lists or databases of the names, addresses, phone numbers, and 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.
International Research
Availability of sampling frames varies dramatically around the world.
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11. 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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12. 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 study’s design and the correctness of execution.
It is not due to chance fluctuation.
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13. Random Sampling and Nonsampling Errors (cont’d)
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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14. EXHIBIT 16.4 Errors Associated with Sampling
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15. Probability versus Nonprobability 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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16. 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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17. Nonprobability Sampling (cont’d)
Possible Sources Of Bias
Respondents chosen because they were:
Similar to interviewer
Easily found
Willing to be interviewed
Middle-class
Advantages of Quota Sampling
Speed of data collection
Lower costs
Convenience
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18. Nonprobability Sampling (cont’d)
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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19. Probability Sampling Simple Random Sampling Systematic 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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20. 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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21. EXHIBIT 16.5 Disproportional Sampling: Hypothetical Example
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22. 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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23. EXHIBIT 16.6 Examples of Clusters
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24. 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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25. EXHIBIT 16.8 Geographic Hierarchy Inside Urbanized Areas
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26. What Is the Appropriate Sample Design?
National vs. Local
Knowledge of Population
Time
Resources
Degree of Accuracy
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27. EXHIBIT 16.9 Comparison of Sampling Techniques: Nonprobability Samples
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28. EXHIBIT 16.10 Comparison of Sampling Techniques: Probability Samples
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