1. CHAPTER 12 – SAMPLING DESIGNS AND SAMPLING PROCEDURES Zikmund & Babin Essentials of Marketing Research – 5 th Edition © 2013 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.12–1

2. © 2013 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.12–2 LEARNING OUTCOMES 1.Explain reasons for taking a sample rather than a complete census 2.Describe the process of identifying a target population and selecting a sampling frame 3.Compare random sampling and systematic (nonsampling) errors with an emphasis on how the Internet is intertwined with this issue 4.Identify the types of nonprobability sampling, including their advantages and disadvantages 5.Summarize the various types of probability samples 6.Discuss how to choose an appropriate sample design After studying this chapter, you should be able to

3. © 2013 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.12–3 Introduction 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.

4. © 2013 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.12–4 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.

5. © 2013 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.12–5 Identifying a Relevant Population and Sampling Frame 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.

6. © 2013 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.12–6 Identifying a Relevant Population and Sampling Frame (cont’d) Sampling Frame (cont’d)  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.  Online Panels  Lists of respondents who have agreed to participate in marketing research via e-mail.  International Research  Availability of sampling frames varies dramatically around the world.

7. © 2013 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.12–7 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.

8. © 2013 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.12–8 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.

9. © 2013 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.12–9 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.

10. © 2013 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.12–10 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.

11. © 2013 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.12–11 Nonprobability Sampling (cont’d) Possible Sources Of Bias with Quota Sampling  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

12. © 2013 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.12–12 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.

13. © 2013 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.12–13 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.

14. © 2013 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.12–14 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.

15. © 2013 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.12–15 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.

16. © 2013 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.12–16 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.

17. © 2013 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.12–17 What is the Appropriate Sample Design? Criteria considered:  Degree of accuracy  Resources  Time  Advance knowledge of the population  National versus local project