2 Sampling Terminology Sample Population or universe Population element A subset, or some part, of a larger populationPopulation or universeAny complete group of entities that share some common set of characteristicsPopulation elementAn individual member of a populationCensusAn investigation of ALL the individual elements that make up a population
3 A puzzle is a sample until it’s done A puzzle is a sample until it’s done. The sample allows one to guess at the picture.
4 Why Sample? Pragmatic Reasons Accurate and Reliable Results Budget & time constraints.Limited access to total population.Accurate and Reliable ResultsSamples can yield reasonably accurate information.Strong similarities in population elements makes sampling possible.Sampling may be more accurate than a census.Destruction of Test UnitsSampling reduces the costs of research in finite populations.
5 Table 12.1 Sample Versus Census Sample vs. CensusTable 12.1 Sample Versus Census
7 Identifying a Relevant Population Defining the Target PopulationWhat is the relevant population?Whom do we want to talk to?Population is operationally defined by specific & explicit tangible characteristics.If you want to target “Women”, do you meanAll women still capable of bearing children or,All women between the ages of 12 and 50?
8 Identifying a Sampling Frame A list of elements from which a sample may be drawnAlso called the working population.Sampling Frame Error occurs when certain sample elementsare not listed, orare not accurately represented in a sampling frame.Sampling services (list brokers)Provide lists or databases of the names, addresses, phone numbers, & addresses of specific populations.Reverse directoryA directory similar to a telephone directory except that listings are by city & street address or by phone number rather than alphabetical by last name.Online PanelsLists of respondents who have agreed to participate in marketing research via .International ResearchAvailability of sampling frames varies dramatically around the world.
9 Sampling Units Sampling Unit Primary Sampling Unit (PSU) 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 UnitA unit selected in the second stage of sampling.Tertiary Sampling UnitA unit selected in the third stage of sampling.
10 Random Sampling & Nonsampling Errors Random Sampling ErrorThe difference between the sample result & 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.Probability of such error increases as sample size decreases.Systematic Sampling ErrorSystematic (nonsampling) error results from nonsampling factors, primarily the nature of a study’s design & the correctness of execution.It is not due to chance fluctuation.Probability of such error increases as sample size increases.
12 Two Major Categories of Sampling Probability samplingKnown, nonzero, & equal probability of selection for every population elementNonprobability samplingProbability of selecting any particular member is unknown
13 Nonprobability Sampling Convenience SamplingObtaining people or units that are most conveniently available.Judgment (Purposive) SamplingExperienced individual selects sample based on personal judgment about some appropriate characteristic of the sample member.Quota SamplingEnsures that various subgroups of a population will be represented on pertinent characteristics to the exact extent that the investigator desires.Snowball SamplingA sampling procedure in which initial respondents are selected by probability methods and additional respondents are obtained from information provided by the initial respondents.
14 Comparing the Nonprobability Techniques StrengthsWeaknessesConvenience SamplingLeast expensiveLeast time neededMost convenientSelection biasNot representativeJudgmental SamplingLow expenseLittle time neededConvenientHighly SubjectiveDoes not allow generalizationsQuota SamplingCan control sample characteristicsGreatest probability of representative sampleMost likely not representativeSnowball SamplingCan estimate rare characteristicsTime consuming
15 Figure 12.8 Probability Sampling Techniques Most Commonly-UsedProbability Sampling TechniquesFigure Probability Sampling TechniquesProbability Sampling TechniquesSimple RandomSamplingSystematicSamplingStratifiedSamplingProportional vs. Disproportional SamplingCluster Sampling
16 Probability Sampling Simple Random Sampling Systematic Sampling Assures each element in the population of an equal chance of being included in the sample.Systematic SamplingA starting point is selected by a random process and then every nth number on the list is selected.Stratified SamplingSimple random subsamples that are more or less equal on some characteristic are drawn from within each stratum of the population.
18 Proportional vs. Disproportional Sampling Proportional Stratified SampleNumber of sampling units drawn from each stratum is in proportion to population size of that stratum.Disproportional Stratified SampleSample size for each stratum is allocated according to analytical considerations.
20 Cluster SamplingEconomically efficient sampling technique in which primary sampling unit is not the individual element in the population but a large cluster of elements.Clusters are selected randomly.
22 What is the Appropriate Sample Design? It Depends Degree of accuracyResourcesTimeAdvanced knowledge of the populationNational versus localNeed for statistical analysis
23 Internet Samples Recruited Ad Hoc Samples Opt-in Lists Potential subjects unaware they might be asked to participate in a studyLess expensiveLower selection biasOpt-in ListsPotential subjects know they might be asked to participate in studies as they have previously agreed to receive such invitations.More expensiveGreater chance of selection bias“Much Better” response rates (????)
24 Sample Size Bigger Is Better — Right? One study indicates that 60% of consumers believe that there is too much violence in video games, but another study suggests that 75% of parents do not believe it harms children.Another shows that 40% of Nintendo owners are highly likely to buy a new game that has been concept tested.How good are these descriptive statistics? Consider the sample!
25 Information Needed to Determine Sample Size Variance (standard deviation)A heterogeneous population has more variance (a larger standard deviation) which will require a larger sample.A homogeneous population has less variance (a smaller standard deviation) which permits a smaller sample.Get from pilot study or rule of thumb (managerial judgment)Magnitude of errorHow precise must the estimate be?Managerial judgment or calculationConfidence levelHow much error will be tolerated?Managerial judgmentMost commonly used standards are a 95% confidence level (Z score = 1.96), or 99% confidence level (Z score = 2.57).
26 Sample Size Formula for Questions Involving an Analysis of Means
27 Sample Size Formula - Example Suppose a survey researcher is studying expenditures on lipstickWishes to have a 95 percent confident level (Z) andRange of error (E) of less than $2.00.The estimate of the standard deviation is $29.00.
33 Sample Size for a Proportion: Example A researcher believes that a simple random sample will show that 60 percent of a population (p = .6) recognizes the name of an automobile dealership.Note that 40% of the population would not recognize the dealership’s name (q = .4)The researcher wants to estimate with 95% confidence (Z = 1.96) that the allowance for sampling error is not greater than 3.5 percentage points (E = 0.035)
34 Calculating Sample Size at the 95% Confidence Level 753=001225.922)24)(.84163(035( .46(.961.nqp2