Copyright © 2008 by Nelson, a division of Thomson Canada Limited Chapter 14 Part 4 Sampling and Data Collection SAMPLING DESIGNS AND SAMPLING PROCEDURES

LEARNING OBJECTIVES 1.To define the terms sample, population, population element, and census 2.To explain why a sample rather than a complete census may be taken 3.To discuss the issues concerning the identification of the target population and the selection of a sampling frame 4.To discuss common forms of sampling frames and sampling frame error 5.To distinguish between random sampling and systematic (nonsampling) errors What you will learn in this chapter Copyright © 2008 by Nelson, a division of Thomson Canada Limited 14–1

LEARNING OBJECTIVES (cont’d) 6.To explain the various types of systematic (nonsampling) errors that result from sample selection 7.To discuss the advantages and disadvantages of the various types of probability and nonprobability samples 8.To understand how to choose an appropriate sample design What you will learn in this chapter Copyright © 2008 by Nelson, a division of Thomson Canada Limited 14–2

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 Sampling Terminology Copyright © 2008 by Nelson, a division of Thomson Canada Limited 14–3

Pragmatic ReasonsPragmatic Reasons  Sampling cuts costs, reduces labour requirements, and gathers vital information quickly Accurate and Reliable ResultsAccurate and Reliable Results  Most properly selected samples give sufficiently accurate results  If the elements of a population are quite similar, only a small sample is necessary to accurately portray the characteristic of interest Why Sample? Copyright © 2008 by Nelson, a division of Thomson Canada Limited 14–4

Defining the Target PopulationDefining the Target Population  Answering questions about the crucial characteristics of the population is the usual technique for defining the target population Practical Sampling Concepts Copyright © 2008 by Nelson, a division of Thomson Canada Limited 14–5

The Sampling FrameThe Sampling Frame  A list of elements from which a sample may be drawn; also called working population  Sampling frame error  An error that occurs when certain sample elements are not listed or are not accurately represented in a sampling frame  Sampling frames for international marketing research  The availability of sampling frames around the globe varies dramatically  Not every country’s government conducts a census of population Practical Sampling Concepts (cont’d) Copyright © 2008 by Nelson, a division of Thomson Canada Limited 14–6

Sampling UnitsSampling Units  Sampling unit  A single element or group of elements subject to selection in the sample  Primary sampling unit (PSU)  A term used to designate a unit selected in the first stage of sampling  Secondary sampling unit  A term used to designate a unit selected in the second stage of sampling  Tertiary sampling unit  A term used to designate a unit selected in the third stage of sampling Practical Sampling Concepts (cont’d) Copyright © 2008 by Nelson, a division of Thomson Canada Limited 14–7

Random Sampling ErrorRandom Sampling Error  The difference between 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 (Nonsampling) ErrorSystematic (Nonsampling) Error  Error resulting from some imperfect aspect of the research design, such as mistakes in sample selection, sampling frame error, or nonresponses from persons who were not contacted or refused to participate Random Sampling and Nonsampling Errors Copyright © 2008 by Nelson, a division of Thomson Canada Limited 14–9

Random Sampling and Nonsampling Errors (cont’d) Less Than Perfectly Representative SamplesLess Than Perfectly Representative Samples  Nonresponse error  The statistical differences between a survey that includes only those who responded and a perfect survey that would also include those who failed to respond Copyright © 2008 by Nelson, a division of Thomson Canada Limited 14–10

Probability SamplingProbability Sampling  A sampling technique in which every member of the population has a known, non-zero 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 Probability Versus Nonprobability Sampling Copyright © 2008 by Nelson, a division of Thomson Canada Limited 14–11

Convenience SamplingConvenience Sampling  The sampling procedure of obtaining those people or units that are most conveniently available Purposive (Judgment) SamplingPurposive (Judgment) Sampling  A nonprobability sampling technique in which an experienced individual selects the sample based on personal judgment about some appropriate characteristic of the sample member Nonprobability Sampling Copyright © 2008 by Nelson, a division of Thomson Canada Limited 14–12

Snowball (Referral) SamplingSnowball (Referral) 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 Nonprobability Sampling (cont’d) Copyright © 2008 by Nelson, a division of Thomson Canada Limited 14–13

Quota SamplingQuota Sampling  A nonprobability sampling procedure that ensures that various subgroups of a population will be represented on pertinent characteristics to the exact extent that the investigator desires  Possible sources of bias  Because respondents are selected according to a convenience sampling procedure rather than on a probability basis, the haphazard selection of subjects may introduce bias  Advantages of quota sampling  Speed of data collection, lower costs, and convenience Nonprobability Sampling (cont’d) Copyright © 2008 by Nelson, a division of Thomson Canada Limited 14–14

Simple Random SamplingSimple Random Sampling  A sampling procedure that assures each element in the population of an equal chance of being included in the sample  Selecting a simple random sample  Example: Honda Systematic SamplingSystematic Sampling  A sampling procedure in which a starting point is selected by a random process and then every nth number on the list is selected Probability Sampling Copyright © 2008 by Nelson, a division of Thomson Canada Limited 14–15

Stratified SamplingStratified Sampling  A probability sampling procedure in which simple random subsamples that are more or less equal on some characteristic are drawn from within each stratum of the population Proportional versus Disproportional SamplingProportional versus Disproportional Sampling  Proportional stratified sample  A stratified sample in which the number of sampling units drawn from each stratum is in proportion to the population size of that stratum  Disproportional stratified sample  A stratified sample in which the sample size for each stratum is allocated according to analytical considerations Probability Sampling (cont’d) Copyright © 2008 by Nelson, a division of Thomson Canada Limited 14–16

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 Multistage Area SamplingMultistage Area Sampling  Sampling that involves using a combination of two or more probability sampling techniques Probability Sampling (cont’d) Copyright © 2008 by Nelson, a division of Thomson Canada Limited 14–17

Degree of AccuracyDegree of Accuracy  The degree of accuracy required or the researcher’s tolerance for sampling and nonsampling error may vary from project to project, especially when cost savings or another benefit may be a trade-off for a reduction in accuracy ResourcesResources  If the researcher’s financial and human resources are restricted, certain options will have to be eliminated What Is the Appropriate Sample Design? Copyright © 2008 by Nelson, a division of Thomson Canada Limited 14–19

What Is the Appropriate Sample Design? (cont’d) TimeTime  A researcher who needs to meet a deadline or complete a project quickly will be more likely to select a simple, less time-consuming sample design Advance Knowledge of the PopulationAdvance Knowledge of the Population  Advance knowledge of population characteristics is an important criterion  A lack of adequate lists may rule out systematic sampling or stratified sampling, or may dictate that a preliminary study be conducted to generate information to build a sampling frame Copyright © 2008 by Nelson, a division of Thomson Canada Limited 14–20

What Is the Appropriate Sample Design? (cont’d) National versus Local ProjectNational versus Local Project  Geographic proximity of population elements will influence sample design Need for Statistical AnalysisNeed for Statistical Analysis  The need for statistical projections based on the sample often is a criterion Copyright © 2008 by Nelson, a division of Thomson Canada Limited 14–21

Web Site VisitorsWeb Site Visitors  Internet surveys may not be representative because of the haphazard manner by which many respondents arrived at a particular Web site or because of self-selection bias Panel SamplesPanel Samples  Drawing a probability sample from an established consumer panel or other prerecruited membership panel is a popular, scientific, and effective method for creating a sample of Internet users Internet Sampling Is Unique Copyright © 2008 by Nelson, a division of Thomson Canada Limited 14–22

Recruited Ad Hoc SamplesRecruited Ad Hoc Samples  Another means of obtaining an Internet sample is to obtain or create a sampling frame of addresses on an ad hoc basis  Researchers may create the sampling frame offline or online Opt-in ListsOpt-in Lists  Opt in  To give permission to receive selected , such as questionnaires, from a company with an Internet presence Internet Sampling Is Unique (cont’d) Copyright © 2008 by Nelson, a division of Thomson Canada Limited 14–23