## Presentation on theme: "Chapter 16 Sampling Designs and Sampling Procedures © 2010 South-Western/Cengage Learning. All rights reserved. May not be scanned, copied or duplicated,"— Presentation transcript:

Chapter 16 Sampling Designs and Sampling Procedures © 2010 South-Western/Cengage Learning. All rights reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. ZIKMUND BABIN CARR GRIFFIN BUSINESS MARKET RESEARCH EIGHTH EDITION

© 2010 South-Western/Cengage Learning. All rights reserved. May not be scanned, copied or duplicated, or posted to a publically accessible website, in whole or in part.16–2 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 4.Identify the types of nonprobability sampling, including their advantages and disadvantages After studying this chapter, you should be able to

© 2010 South-Western/Cengage Learning. All rights reserved. May not be scanned, copied or duplicated, or posted to a publically accessible website, in whole or in part.16–3 LEARNING OUTCOMES (cont’d) 5.Summarize the advantages and disadvantages of the various types of probability samples 6.Discuss how to choose an appropriate sample design, as well as challenges for Internet sampling After studying this chapter, you should

© 2010 South-Western/Cengage Learning. All rights reserved. May not be scanned, copied or duplicated, or posted to a publically accessible website, in whole or in part.16–4 Sampling Terminology SampleSample  A subset, or some part, of a larger population. Population (universe)Population (universe)  Any complete group of entities that share some common set of characteristics. Population ElementPopulation Element  An individual member of a population. CensusCensus  An investigation of all the individual elements that make up a population.

© 2010 South-Western/Cengage Learning. All rights reserved. May not be scanned, copied or duplicated, or posted to a publically accessible website, in whole or in part.16–5 Why Sample? Pragmatic ReasonsPragmatic Reasons  Budget and time constraints.  Limited access to total population. Accurate and Reliable ResultsAccurate 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 UnitsDestruction of Test Units  Sampling reduces the costs of research in finite populations.

© 2010 South-Western/Cengage Learning. All rights reserved. May not be scanned, copied or duplicated, or posted to a publically accessible website, in whole or in part.16–6 EXHIBIT 16.1 A Photographic Example of How Sampling Works

© 2010 South-Western/Cengage Learning. All rights reserved. May not be scanned, copied or duplicated, or posted to a publically accessible website, in whole or in part.16–7 EXHIBIT 16.2 Stages in the Selection of a Sample

© 2010 South-Western/Cengage Learning. All rights reserved. May not be scanned, copied or duplicated, or posted to a publically accessible website, in whole or in part.16–8 Practical Sampling Concepts Defining the Target PopulationDefining 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 FrameThe 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.

© 2010 South-Western/Cengage Learning. All rights reserved. May not be scanned, copied or duplicated, or posted to a publically accessible website, in whole or in part.16–9 EXHIBIT 16.3 Mailing List Directory Page

© 2010 South-Western/Cengage Learning. All rights reserved. May not be scanned, copied or duplicated, or posted to a publically accessible website, in whole or in part.16–10 Practical Sampling Concepts (cont’d) Sampling services (list brokers)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. International ResearchInternational Research  Availability of sampling frames varies dramatically around the world.

© 2010 South-Western/Cengage Learning. All rights reserved. May not be scanned, copied or duplicated, or posted to a publically accessible website, in whole or in part.16–11 Sampling Units Sampling UnitSampling 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.

© 2010 South-Western/Cengage Learning. All rights reserved. May not be scanned, copied or duplicated, or posted to a publically accessible website, in whole or in part.16–12 Random Sampling and Nonsampling Errors Random Sampling ErrorRandom 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 ErrorSystematic 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.

© 2010 South-Western/Cengage Learning. All rights reserved. May not be scanned, copied or duplicated, or posted to a publically accessible website, in whole or in part.16–13 Random Sampling and Nonsampling Errors (cont’d) Less than Perfectly Representative SamplesLess 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.

© 2010 South-Western/Cengage Learning. All rights reserved. May not be scanned, copied or duplicated, or posted to a publically accessible website, in whole or in part.16–14 EXHIBIT 16.4 Errors Associated with Sampling

© 2010 South-Western/Cengage Learning. All rights reserved. May not be scanned, copied or duplicated, or posted to a publically accessible website, in whole or in part.16–15 Probability versus Nonprobability Sampling Probability SamplingProbability Sampling  A sampling technique in which every member of the population has a known, nonzero probability of selection. Nonprobability SamplingNonprobability 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.

© 2010 South-Western/Cengage Learning. All rights reserved. May not be scanned, copied or duplicated, or posted to a publically accessible website, in whole or in part.16–16 Nonprobability Sampling Convenience SamplingConvenience Sampling  Obtaining those people or units that are most conveniently available. Judgment (Purposive) SamplingJudgment (Purposive) Sampling  An experienced individual selects the sample based on personal judgment about some appropriate characteristic of the sample member. Quota SamplingQuota Sampling  Ensures that various subgroups of a population will be represented on pertinent characteristics to the exact extent that the investigator desires.

© 2010 South-Western/Cengage Learning. All rights reserved. May not be scanned, copied or duplicated, or posted to a publically accessible website, in whole or in part.16–17 Nonprobability Sampling (cont’d) Possible Sources Of BiasPossible Sources Of Bias  Respondents chosen because they were:  Similar to interviewer  Easily found  Willing to be interviewed  Middle-class Advantages of Quota SamplingAdvantages of Quota Sampling  Speed of data collection  Lower costs  Convenience

© 2010 South-Western/Cengage Learning. All rights reserved. May not be scanned, copied or duplicated, or posted to a publically accessible website, in whole or in part.16–18 Nonprobability Sampling (cont’d) Snowball SamplingSnowball 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.

© 2010 South-Western/Cengage Learning. All rights reserved. May not be scanned, copied or duplicated, or posted to a publically accessible website, in whole or in part.16–19 Probability Sampling Simple Random SamplingSimple Random Sampling  Assures each element in the population of an equal chance of being included in the sample. Systematic SamplingSystematic Sampling  A starting point is selected by a random process and then every nth number on the list is selected. Stratified SamplingStratified Sampling  Simple random subsamples that are more or less equal on some characteristic are drawn from within each stratum of the population.

© 2010 South-Western/Cengage Learning. All rights reserved. May not be scanned, copied or duplicated, or posted to a publically accessible website, in whole or in part.16–20 Proportional versus Disproportional Sampling Proportional Stratified SampleProportional Stratified Sample  The number of sampling units drawn from each stratum is in proportion to the population size of that stratum. Disproportional Stratified SampleDisproportional Stratified Sample  The sample size for each stratum is allocated according to analytical considerations.

© 2010 South-Western/Cengage Learning. All rights reserved. May not be scanned, copied or duplicated, or posted to a publically accessible website, in whole or in part.16–21 EXHIBIT 16.5 Disproportional Sampling: Hypothetical Example

© 2010 South-Western/Cengage Learning. All rights reserved. May not be scanned, copied or duplicated, or posted to a publically accessible website, in whole or in part.16–22 Cluster Sampling Cluster SamplingCluster 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.

© 2010 South-Western/Cengage Learning. All rights reserved. May not be scanned, copied or duplicated, or posted to a publically accessible website, in whole or in part.16–23 EXHIBIT 16.6 Examples of Clusters

© 2010 South-Western/Cengage Learning. All rights reserved. May not be scanned, copied or duplicated, or posted to a publically accessible website, in whole or in part.16–24 Multistage Area Sampling Multistage Area SamplingMultistage 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.

© 2010 South-Western/Cengage Learning. All rights reserved. May not be scanned, copied or duplicated, or posted to a publically accessible website, in whole or in part.16–25 EXHIBIT 16.8 Geographic Hierarchy Inside Urbanized Areas

© 2010 South-Western/Cengage Learning. All rights reserved. May not be scanned, copied or duplicated, or posted to a publically accessible website, in whole or in part.16–26 What Is the Appropriate Sample Design? Appropriate Sample Design National vs. Local Knowledge of Population TimeTime ResourcesResources Degree of Accuracy

© 2010 South-Western/Cengage Learning. All rights reserved. May not be scanned, copied or duplicated, or posted to a publically accessible website, in whole or in part.16–27 EXHIBIT 16.9 Comparison of Sampling Techniques: Nonprobability Samples

© 2010 South-Western/Cengage Learning. All rights reserved. May not be scanned, copied or duplicated, or posted to a publically accessible website, in whole or in part.16–28 EXHIBIT 16.10 Comparison of Sampling Techniques: Probability Samples