Wk 4 Data CollectionDr. Huei Holloman
Week 4 Objectives
The goal of this research is to discover the real nature of the problem & to suggest newpossible solutions or new ideas.A ...
Chapter 11MeasurementMcGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.
11-7Learning ObjectivesUnderstand . . .• The distinction between measuring objects, properties, andindicants of properties...
11-8Measurements Will Vary Over Time“The only man who behaved sensibly was my tailor; he took mymeasurement anew every tim...
11-9PulsePoint:Research Revelation32.5 The percent of corporationsusing or planning to use cloudcomputing—using softwarean...
Measurement in research consists of:• assigning numbers to empirical events, objects or properties, oractivities in compli...
11-11Characteristics of Measurement
11-12Levels of MeasurementOrdinalintervalRatioNominalClassification
Levels of MeasurementOrdinalintervalRatioNominal ClassificationOrder ( > or < )Classification• Order means that the number...
11-14FromInvestigative toMeasurementQuestions
11-15Ordinal Scales• Ordinal data require conformity to alogical postulate, which states:If a is greater than b, andb is g...
11-16Levels of MeasurementOrdinalintervalRatioNominal ClassificationOrderClassificationOrderClassificationDistance
11-17Levels of MeasurementOrdinalintervalRatioNominalClassificationOrderClassificationOrderClassification DistanceNatural ...
Ratio Scales11-18ExamplesWeightHeightNumber of children• Ratio data : actual amounts of a variable.• E.g., monetary values...
11-19Sources of Error1. Respondents may also suffer from temporary factors like fatigue andboredom.2. Any condition that p...
11-20Evaluating Measurement ToolsCriteriaValidityPracticality Reliability• Validity is the extent to which a test measures...
11-21Understanding Validity and Reliability
Reliability & Validity
11-23Validity DeterminantsContentConstructCriterion
11-24Increasing Content ValidityContentLiteratureSearchExpertInterviewsGroupInterviewsQuestionDatabaseEtc.
11-25Validity DeterminantsContentConstruct
11-26Increasing Construct ValidityNew measure of trustKnown measure of trustEmpathyCredibility
11-27Validity DeterminantsContentConstructCriterion
11-28Judging Criterion ValidityRelevanceFreedom from biasReliabilityAvailabilityCriterion
11-29Reliability EstimatesStabilityInternalConsistencyEquivalence
PracticalityEconomy InterpretabilityConvenience
11-31Key Terms• Internal validity• Interval scale• Mapping rules• Measurement• Nominal scale• Objects• Ordinal scale• Prac...
Chapter 12MeasurementScalesMcGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.
12-33Learning ObjectivesUnderstand…• The nature of attitudes and their relationship to behavior.• The critical decisions i...
12-34Measurements are Relative“Any measurement must take into account theposition of the observer. There is no such thinga...
12-35PulsePoint:Research Revelation34 The percent of workers whoare considered truly loyal.
12-36The ScalingProcess
12-37Nature of AttitudesCognitiveI think oatmeal is healthierthan corn flakes for breakfast.AffectiveBehavioralI hate corn...
Response biases & sampling
Improving Predictability of AttitudesReferencegroupsMultiplemeasuresFactorsStrongSpecificBasisDirectFactors  the applicab...
12-40Measurement Scales“All survey questions must be actionable if you wantresults.”Frank Schmidt, senior scientistThe Gal...
Selecting a Measurement ScaleResearch objectives Response typesData propertiesNumber ofdimensionsForced or unforcedchoices...
12-42Response TypesRating scaleRanking scaleCategorizationSorting
12-43Dimensions-Religion, depression symptoms, democracyUnidimensionalMulti-dimensional
12-44Balanced or UnbalancedVery badBadNeither good nor badGoodVery goodPoorFairGoodVery goodExcellentHow good an actress i...
12-45Forced or Unforced ChoicesVery badBadNeither good nor badGoodVery goodVery badBadNeither good nor badGoodVery goodNo ...
Number of Scale PointsVery badBadNeither good nor badGoodVery goodVery badSomewhat badA little badNeither good nor badA li...
Rater ErrorsError ofcentral tendencyError of leniency•Adjust strength ofdescriptive adjectives•Space intermediatedescripti...
12-48Rater ErrorsPrimacy EffectRecency EffectReverse order ofalternatives periodicallyor randomly
Rater ErrorsHalo Effect• Rate one traitat a time• Reveal one traitper page• Reverse anchorsperiodically• The halo effect i...
12-50Simple Category ScaleI plan to purchase a MindWriter laptop in the12 months. Yes No
12-51Multiple-Choice,Single-Response ScaleWhat newspaper do you read most often for financial news? East City Gazette We...
12-52Multiple-Choice, Multiple-ResponseScaleWhat sources did you use when designing your newhome? Please check all that ap...
12-53Likert ScaleThe Internet is superior to traditional libraries forcomprehensive searches. Strongly disagree Disagree...
Semantic Differential• studies of brand and institutional image, employee morale, safety,financial soundness, trust, etc.•...
Adapting SD ScalesConvenience of Reaching the Store from Your LocationNearby ___: ___: ___: ___: ___: ___: ___: DistantSho...
12-56SD Scale for Analyzing ActorCandidates
12-57Graphic of SD Analysis
Numerical Scale• Numerical scales have equal intervals that separate their numericscale points. The verbal anchors serve a...
Multiple Rating ListScales“Please indicate how important or unimportant each service characteristic is:”IMPORTANT UNIMPORT...
• Used as an alternative to the semantic differential, especially when itis difficult to find bipolar adjectives that matc...
Constant-SumScales• The participant allocates points to more than one attribute or property indicant,such that they total ...
12-62Graphic Rating Scales
12-63Ranking Scales(see next slides…)Paired-comparison scaleForced ranking scaleComparative scale
Paired-Comparison Scale
Forced RankingScale• This method is faster than paired comparisons and is usually easier andmore motivating to the partici...
12-66Comparative Scale
Sorting
12-68MindWriter ScalingLikert ScaleThe problem that prompted service/repair was resolvedStronglyDisagree DisagreeNeither A...
12-69Ideal Scalogram Pattern (social distance, organizationalhierarchies, and evolutionary product stages)ItemParticipantS...
Key Terms• Attitude• Balanced rating scale• Categorization• Comparative scale• Constant-sum scale• Cumulative scale• Error...
12-71Key Terms• Sorting• Stapel scale• Summated rating scale• Unbalanced rating scale• Unforced-choice rating scale• Unidi...
Chapter 13QuestionnairesandInstrumentsMcGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Res...
13-73Learning ObjectivesUnderstand...• The link forged between the management dilemma and thecommunication instrument by t...
13-74Learning ObjectivesUnderstand . . .• The influence of question content, question wording,response strategy, and preli...
13-75Measurement Skepticism“Research that asks consumers what they did and why isincredibly helpful. Research that asks co...
13-76PulsePoint:Research Revelation60 The percent of businesses hitannually by cybercrime.
13-77Overall Flowchart for Instrument Design
13-78Flowchart for Instrument Design Phase 1
Strategic Concerns in Instrument DesignWhat type of scale is needed?What communication approach will be used?Should the qu...
13-80Technology AffectsQuestionnaire DevelopmentWebSurveyor used to write an instrument.Write questionnaires more quicklyC...
13-81Disguising StudyObjectivesSituationswheredisguise isunnecessaryWillingly shared,Conscious-levelinformationReluctantly...
13-82Dummy Table for American Eating HabitsAgeUse of Convenience FoodsAlwaysUseUseFrequentlyUseSometimes Rarely Use Never ...
13-83Flowchart for Instrument Design Phase 2
Question Categories and StructureAdministrative Target Classification3 categories of measurement questions.1. Administrati...
13-85Engagement = Convenience“Participants are becoming more and moreaware of the value of their time. The key tomaintaini...
13-86Question ContentShould this question be asked?Is the question of proper scope and coverage?Can the participant adequa...
Criteria of Question WordingCriteriaSharedvocabulary SinglemeaningMisleadingassumptionsAdequatealternativesPersonalizedBia...
Response StrategyFactorsObjectivesof the studyParticipant’s levelof informationDegree to which participantshave thought th...
13-89Free-Response Strategy - open-ended questionsWhat factors influenced your enrollment in Metro U?_____________________...
Dichotomous Response StrategyDid you attend the “A Day at College”program at Metro U?YesNoWhich one of the following fac...
Checklist Response StrategyWhich of the following factors influenced your decision to enroll in Metro U?(Check all that ap...
RankingPlease rank-order your top three factors from the following list based on theirinfluence in encouraging you to appl...
13-93Summary of Scale TypesType Restrictions ScaleItemsData TypeRating ScalesSimple CategoryScale• Needs mutually exclusiv...
13-94Summary of Scale TypesType Restrictions Scale Items Data TypeRating ScalesNumericalScaleNeeds concepts with standardi...
Summary of Scale TypesType Restrictions Scale Items Data TypeRating ScalesStapel Scale Needs verbal labels that areoperati...
Internet Survey Scale Options
13-97Internet Survey Scale Options
13-98Internet SurveyScale Options
Sources of Questions• Handbook of Marketing Scales• The Gallup Poll CumulativeIndex• Measures of Personality andSocial-Psy...
13-100Flowchart forInstrument DesignPhase 3
13-101Guidelines for Question SequencingInteresting topics earlySimple topics earlySensitive questions laterClassification...
13-102Illustrating the Funnel Approach1. How do you think this country is getting along in its relations withother countri...
13-103Branching Question
13-104Components of Questionnaires
13-105MindWriter Survey
13-106Overcoming Instrument ProblemsBuild rapportRedesign question processExplore alternativesUse other methodsPretest
13-107Key Terms• Administrative question• Branched question• Buffer question• Checklist• Classification question• Dichotom...
Chapter 14SamplingMcGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.
14-109Small Samples Can Enlighten“The proof of the pudding is in the eating.By a small sample we may judge of thewhole pie...
14-110PulsePoint:Research Revelation80 The average number of textmessages sent per day byAmerican teens.
Sampling Methods
14-112The Nature of Sampling•Population•Population Element•Census•Sample•Sampling frame
14-113Why Sample?GreateraccuracyAvailability ofelementsGreaterspeedSamplingprovidesLower cost
14-114What Is a Sufficiently Large Sample?“In recent Gallup ‘Poll on polls,’ . . . When asked about thescientific sampling...
14-115When Is a Census Appropriate?NecessaryFeasible
14-116What Is a Valid Sample?Accurate Precise
14-117Sampling Designwithin the Research Process
14-118Types of Sampling DesignsElement Selection Probability NonprobabilityUnrestricted Simple random ConvenienceRestricte...
14-119Steps in Sampling DesignWhat is the target population?What are the parameters of interest?What is the sampling frame...
14-120When to Use Larger Sample?DesiredprecisionNumber ofsubgroupsConfidencelevelPopulationvarianceSmall errorrange
Simple RandomAdvantages• Easy to implement withrandom dialingDisadvantages• Requires list of populationelements• Time cons...
14-122StratifiedAdvantages• Control of sample size in strata• Increased statistical efficiency• Provides data to represent...
14-123ClusterAdvantages• Provides an unbiased estimateof population parameters ifproperly done• Economically more efficien...
14-124Stratified and Cluster SamplingStratified• Population divided into fewsubgroups• Homogeneity within subgroups• Heter...
14-125Area Sampling
14-126Double SamplingAdvantages• May reduce costs if first stageresults in enough data tostratify or cluster the populatio...
14-127Nonprobability SamplesCostFeasibilityTimeNo need togeneralizeLimited objectives
14-128Nonprobability Sampling MethodsConvenienceJudgmentQuotaSnowball
14-129Key Terms• Area sampling• Census• Cluster sampling• Convenience sampling• Disproportionate stratifiedsampling• Doubl...
Appendix 14aDetermining SampleSizeMcGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.
14-131Random Samples
14-132Increasing Precision
14-133Confidence Levels & the NormalCurve
14-134Standard ErrorsStandard Error(Z score)% of Area ApproximateDegree ofConfidence1.00 68.27 68%1.65 90.10 90%1.96 95.00...
14-135Central Limit Theorem
14-136Estimates of Dining VisitsConfidence Z score % of Area Interval Range(visits per month)68% 1.00 68.27 9.48-10.5290% ...
14-137Calculating Sample Size for Questions involvingMeansPrecisionConfidence levelSize of interval estimatePopulation Dis...
14-138Metro U Sample Size for MeansSteps InformationDesired confidence level 95% (z = 1.96)Size of the interval estimate ...
14-139Proxies of the Population Dispersion• Previous research on the topic• Pilot test or pretest• Rule-of-thumb calculati...
14-140Metro U Sample Size for ProportionsSteps InformationDesired confidence level 95% (z = 1.96)Size of the interval esti...
14-141Appendix 14a: Key Terms• Central limit theorem• Confidence interval• Confidence level• Interval estimate• Point esti...
Addendum: KeynoteCloseUpMcGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.
14-143Keynote Experiment
14-144Keynote Experiment (cont.)
DeterminingSample SizeAppendix 14aMcGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.
14-146Random Samples
14-147Confidence Levels
14-148Metro U. Dining Club Study
4 research design + sampling methods dr. hueihsia holloman
4 research design + sampling methods dr. hueihsia holloman
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4 research design + sampling methods dr. hueihsia holloman

  1. 1. Wk 4 Data CollectionDr. Huei Holloman
  2. 2. Week 4 Objectives
  3. 3. The goal of this research is to discover the real nature of the problem & to suggest newpossible solutions or new ideas.A food manufacturer wants to know the demographics of people who purchase organic foods.A firm is considering hiring American celebrity Paris Hilton to endorse its products.British Airways would like to test in-flight Internet services on one of its regular flights from NewYork to Tokyo. The company charges $30 one week and $15 the next week.This type of study attempts to discover answers to the following questions: who, what, when,where, or how much.A manufacturer investigates whether consumers will buy a new pill that replaces eating a meal.Cosmopolitan magazine sends out a cover in selected markets featuring a female model tohalf of its readers and a cover with a female and male model to the other half of its readers totest differences in purchase response between the two groups.A hair-care manufacturer interviews wholesalers, retailers, and customers to determine thepotential for a new shampoo package.This type of research attempts to capture a population’s characteristics by making inferencefrom a sample’s characteristics and testing hypotheses.DescriptiveOn the CBS television show Undercover Boss, top executives disguised as middle level orlower
  4. 4. Chapter 11MeasurementMcGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.
  5. 5. 11-7Learning ObjectivesUnderstand . . .• The distinction between measuring objects, properties, andindicants of properties.• The similarities and differences between the four scale types used inmeasurement and when each is used.• The four major sources of measurement error.• The criteria for evaluating good measurement.
  6. 6. 11-8Measurements Will Vary Over Time“The only man who behaved sensibly was my tailor; he took mymeasurement anew every time he saw me, while all the restwent on with their old measurements and expected them to fit me.”George Bernard Shawplaywright and essayist
  7. 7. 11-9PulsePoint:Research Revelation32.5 The percent of corporationsusing or planning to use cloudcomputing—using softwareand server space via Internetsources.
  8. 8. Measurement in research consists of:• assigning numbers to empirical events, objects or properties, oractivities in compliance w/ a set of rules.• Textbook uses an example of auto show attendance.• A mapping rule is a scheme for assigning numbers to aspects of anempirical event.
  9. 9. 11-11Characteristics of Measurement
  10. 10. 11-12Levels of MeasurementOrdinalintervalRatioNominalClassification
  11. 11. Levels of MeasurementOrdinalintervalRatioNominal ClassificationOrder ( > or < )Classification• Order means that the numbers are ordered. One number isgreater than, less than, or equal to another number.E.g., Pizza Hut is better than Papa Johns, ranking
  12. 12. 11-14FromInvestigative toMeasurementQuestions
  13. 13. 11-15Ordinal Scales• Ordinal data require conformity to alogical postulate, which states:If a is greater than b, andb is greater than c, thena is greater than c.• The appropriate measure of centraltendency is the median. The median isthe midpoint of a distribution. Apercentile or quartile reveals thedispersion.
  14. 14. 11-16Levels of MeasurementOrdinalintervalRatioNominal ClassificationOrderClassificationOrderClassificationDistance
  15. 15. 11-17Levels of MeasurementOrdinalintervalRatioNominalClassificationOrderClassificationOrderClassification DistanceNatural OriginOrderClassification Distance
  16. 16. Ratio Scales11-18ExamplesWeightHeightNumber of children• Ratio data : actual amounts of a variable.• E.g., monetary values, population counts, distances, return rates, andamounts of time.• Central tendency and coefficients of variation may also be calculated.• Higher levels of measurement generally yield more information and areappropriate for more powerful statistical procedures.
  17. 17. 11-19Sources of Error1. Respondents may also suffer from temporary factors like fatigue andboredom.2. Any condition that places a strain on the interview3. The interviewer can distort responses by rewording, paraphrasing, orreordering questions.• Stereotypes in appearance and action also introduce bias.• Careless mechanical processing will distort findings and can alsointroduce problems in the data analysis stage through incorrectcoding, careless tabulation, and faulty statistical calculation.4. A defective instrument• confusing and ambiguous.• not explore all the potentially important issues.
  18. 18. 11-20Evaluating Measurement ToolsCriteriaValidityPracticality Reliability• Validity is the extent to which a test measures what we actually wish tomeasure.• Reliability refers to the accuracy and precision of a measurementprocedure.• Practicality is concerned with a wide range of factors of economy,convenience, and interpretability.
  19. 19. 11-21Understanding Validity and Reliability
  20. 20. Reliability & Validity
  21. 21. 11-23Validity DeterminantsContentConstructCriterion
  22. 22. 11-24Increasing Content ValidityContentLiteratureSearchExpertInterviewsGroupInterviewsQuestionDatabaseEtc.
  23. 23. 11-25Validity DeterminantsContentConstruct
  24. 24. 11-26Increasing Construct ValidityNew measure of trustKnown measure of trustEmpathyCredibility
  25. 25. 11-27Validity DeterminantsContentConstructCriterion
  26. 26. 11-28Judging Criterion ValidityRelevanceFreedom from biasReliabilityAvailabilityCriterion
  27. 27. 11-29Reliability EstimatesStabilityInternalConsistencyEquivalence
  28. 28. PracticalityEconomy InterpretabilityConvenience
  29. 29. 11-31Key Terms• Internal validity• Interval scale• Mapping rules• Measurement• Nominal scale• Objects• Ordinal scale• Practicality• Properties• Ratio scale• Reliability– Equivalence– Internal consistency– Stability• Validity– Construct– Contents– Criterion-related
  30. 30. Chapter 12MeasurementScalesMcGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.
  31. 31. 12-33Learning ObjectivesUnderstand…• The nature of attitudes and their relationship to behavior.• The critical decisions involved in selecting an appropriatemeasurement scale.• The characteristics and use of rating, ranking, sorting,and other preference scales.
  32. 32. 12-34Measurements are Relative“Any measurement must take into account theposition of the observer. There is no such thingas measurement absolute, there is onlymeasurement relative.”Jeanette Wintersonjournalist and author
  33. 33. 12-35PulsePoint:Research Revelation34 The percent of workers whoare considered truly loyal.
  34. 34. 12-36The ScalingProcess
  35. 35. 12-37Nature of AttitudesCognitiveI think oatmeal is healthierthan corn flakes for breakfast.AffectiveBehavioralI hate corn flakes.I intend to eat more oatmealfor breakfast.“All survey questions must be actionable if you wantresults.”Frank Schmidt, senior scientistThe Gallup Organization
  36. 36. Response biases & sampling
  37. 37. Improving Predictability of AttitudesReferencegroupsMultiplemeasuresFactorsStrongSpecificBasisDirectFactors  the applicability of attitudinal research for business.1. Specific attitudes are better predictors of behavior2. Strong attitudes are better predictors of behavior composed of little intensity ortopic interest.3. Direct experiences with the attitude object produce behavior more reliably.4. Cognitive-based attitudes influence behaviors better than affective-basedattitudes.
  38. 38. 12-40Measurement Scales“All survey questions must be actionable if you wantresults.”Frank Schmidt, senior scientistThe Gallup Organization
  39. 39. Selecting a Measurement ScaleResearch objectives Response typesData propertiesNumber ofdimensionsForced or unforcedchoicesBalanced orunbalancedRater errorsNumber ofscale pointsAttitude scaling: process of assessing an attitudinal disposition using a numberthat represents a person’s score on an attitudinal continuum ranging from anextremely favorable disposition to an extremely unfavorable one.
  40. 40. 12-42Response TypesRating scaleRanking scaleCategorizationSorting
  41. 41. 12-43Dimensions-Religion, depression symptoms, democracyUnidimensionalMulti-dimensional
  42. 42. 12-44Balanced or UnbalancedVery badBadNeither good nor badGoodVery goodPoorFairGoodVery goodExcellentHow good an actress is Angelina Jolie?
  43. 43. 12-45Forced or Unforced ChoicesVery badBadNeither good nor badGoodVery goodVery badBadNeither good nor badGoodVery goodNo opinionDon’t knowHow good an actress is Angelina Jolie?
  44. 44. Number of Scale PointsVery badBadNeither good nor badGoodVery goodVery badSomewhat badA little badNeither good nor badA little goodSomewhat goodVery goodHow good an actress is Angelina Jolie?
  45. 45. Rater ErrorsError ofcentral tendencyError of leniency•Adjust strength ofdescriptive adjectives•Space intermediatedescriptive phrasesfarther apart•Provide smallerdifferencesin meaning betweenterms near theends of the scale•Use more scale points
  46. 46. 12-48Rater ErrorsPrimacy EffectRecency EffectReverse order ofalternatives periodicallyor randomly
  47. 47. Rater ErrorsHalo Effect• Rate one traitat a time• Reveal one traitper page• Reverse anchorsperiodically• The halo effect is the systematic bias that the rater introducesby carrying over a generalized impression of the subject fromone rating to another.e.g., a teacher may expect that a student who did well on thefirst exam to do well on the second.
  48. 48. 12-50Simple Category ScaleI plan to purchase a MindWriter laptop in the12 months. Yes No
  49. 49. 12-51Multiple-Choice,Single-Response ScaleWhat newspaper do you read most often for financial news? East City Gazette West City Tribune Regional newspaper National newspaper Other (specify:_____________)
  50. 50. 12-52Multiple-Choice, Multiple-ResponseScaleWhat sources did you use when designing your newhome? Please check all that apply. Online planning services Magazines Independent contractor/builder Designer Architect Other (specify:_____________)
  51. 51. 12-53Likert ScaleThe Internet is superior to traditional libraries forcomprehensive searches. Strongly disagree Disagree Neither agree nor disagree Agree Strongly agree
  52. 52. Semantic Differential• studies of brand and institutional image, employee morale, safety,financial soundness, trust, etc.• usually with 7 points, by which one or more participants rate one ormore concepts on each scale item.• Proposition: an object can have several dimensional meaning locatedin multidimensional property space, called semantic space.
  53. 53. Adapting SD ScalesConvenience of Reaching the Store from Your LocationNearby ___: ___: ___: ___: ___: ___: ___: DistantShort time required to reach store ___: ___: ___: ___: ___: ___: ___: Long time required to reach storeDifficult drive ___: ___: ___: ___: ___: ___: ___: Easy DriveDifficult to find parking place ___: ___: ___: ___: ___: ___: ___: Easy to find parking placeConvenient to other stores I shop ___: ___: ___: ___: ___: ___: ___: Inconvenient to other stores I shopProducts offeredWide selection of differentkinds of products ___: ___: ___: ___: ___: ___: ___:Limited selection of differentkinds of productsFully stocked ___: ___: ___: ___: ___: ___: ___: UnderstockedUndependable products ___: ___: ___: ___: ___: ___: ___: Dependable productsHigh quality ___: ___: ___: ___: ___: ___: ___: Low qualityNumerous brands ___: ___: ___: ___: ___: ___: ___: Few brandsUnknown brands ___: ___: ___: ___: ___: ___: ___: Well-known brands
  54. 54. 12-56SD Scale for Analyzing ActorCandidates
  55. 55. 12-57Graphic of SD Analysis
  56. 56. Numerical Scale• Numerical scales have equal intervals that separate their numericscale points. The verbal anchors serve as the labels for the extremepoints.• Numerical scales are often 5-point scales but may have 7 or 10points.• The participants write a number from the scale next to each item.• It produces either ordinal or interval data.
  57. 57. Multiple Rating ListScales“Please indicate how important or unimportant each service characteristic is:”IMPORTANT UNIMPORTANTFast, reliable repair 7 6 5 4 3 2 1Service at my location 7 6 5 4 3 2 1Maintenance by manufacturer 7 6 5 4 3 2 1Knowledgeable technicians 7 6 5 4 3 2 1Notification of upgrades 7 6 5 4 3 2 1Service contract after warranty 7 6 5 4 3 2 1Exhibit 12-3: A multiple rating scale is similar to the numericalscale but differs in 2 ways:1) it accepts a circled response from the rater, and2) the layout facilitates visualization of the results.• This scale produces interval data.
  58. 58. • Used as an alternative to the semantic differential, especially when itis difficult to find bipolar adjectives that match the investigativequestion.• interval data.Stapel Scales: 3 attributes of corporate image.
  59. 59. Constant-SumScales• The participant allocates points to more than one attribute or property indicant,such that they total a constant sum, usually 100 or 10.• Participant precision and patience suffer when too many stimuli areproportioned and summed.• A participant’s ability to add may also be taxed.• Its advantage is its compatibility with percent and the fact that alternatives thatare perceived to be equal can be so scored.• This scale produces interval data.
  60. 60. 12-62Graphic Rating Scales
  61. 61. 12-63Ranking Scales(see next slides…)Paired-comparison scaleForced ranking scaleComparative scale
  62. 62. Paired-Comparison Scale
  63. 63. Forced RankingScale• This method is faster than paired comparisons and is usually easier andmore motivating to the participant.• A drawback of this scale is the limited number of stimuli (usually nomore than 7) that can be handed by the participant.• This scale produces ordinal data.
  64. 64. 12-66Comparative Scale
  65. 65. Sorting
  66. 66. 12-68MindWriter ScalingLikert ScaleThe problem that prompted service/repair was resolvedStronglyDisagree DisagreeNeither AgreeNor Disagree AgreeStronglyAgree1 2 3 4 5Numerical Scale (MindWriter’s Favorite)To what extent are you satisfied that the problem that prompted service/repair wasresolved?VeryDissatisfiedVerySatisfied1 2 3 4 5Hybrid Expectation ScaleResolution of the problem that prompted service/repair.Met FewExpectationsMet SomeExpectationsMet MostExpectationsMet AllExpectationsExceededExpectations1 2 3 4 5
  67. 67. 12-69Ideal Scalogram Pattern (social distance, organizationalhierarchies, and evolutionary product stages)ItemParticipantScore2 4 1 3X X X X 4__ X X X 3__ __ X X 2__ __ __ X 1__ __ __ __ 0* X = agree; __ = disagree.
  68. 68. Key Terms• Attitude• Balanced rating scale• Categorization• Comparative scale• Constant-sum scale• Cumulative scale• Error of central tendency• Error of leniency• Forced-choice rating scale• Forced ranking scale• Graphic rating scale• Halo effect• Item analysis• Likert scale• Multidimensional scale• Multiple-choice, multiple-responsescale• Multiple-choice,single-response scale• Multiple rating list• Numerical scale• Paired-comparison scale• Q-sort• Ranking scale• Rating scale• Scaling• Scalogram analysis• Semantic differential• Simple category scale
  69. 69. 12-71Key Terms• Sorting• Stapel scale• Summated rating scale• Unbalanced rating scale• Unforced-choice rating scale• Unidimensional scale
  70. 70. Chapter 13QuestionnairesandInstrumentsMcGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.
  71. 71. 13-73Learning ObjectivesUnderstand...• The link forged between the management dilemma and thecommunication instrument by the management-research questionhierarchy.• The influence of the communication method on instrument design.• The three general classes of information and what each contributesto the instrument.
  72. 72. 13-74Learning ObjectivesUnderstand . . .• The influence of question content, question wording,response strategy, and preliminary analysis planning onquestion construction.• Each of the numerous question design issues influencinginstrument quality, reliability, and validity.• The sources for measurement questions• The importance of pretesting questions and instruments.
  73. 73. 13-75Measurement Skepticism“Research that asks consumers what they did and why isincredibly helpful. Research that asks consumers whatthey are going to do can often be taken with a grain ofsalt.”Al Riesauthor, co-founder, and chairmanRies & Ries.
  74. 74. 13-76PulsePoint:Research Revelation60 The percent of businesses hitannually by cybercrime.
  75. 75. 13-77Overall Flowchart for Instrument Design
  76. 76. 13-78Flowchart for Instrument Design Phase 1
  77. 77. Strategic Concerns in Instrument DesignWhat type of scale is needed?What communication approach will be used?Should the questions be structured?Should the questioning be disguised?
  78. 78. 13-80Technology AffectsQuestionnaire DevelopmentWebSurveyor used to write an instrument.Write questionnaires more quicklyCreate visually driven instrumentsEliminate manual data entrySave time in data analysis
  79. 79. 13-81Disguising StudyObjectivesSituationswheredisguise isunnecessaryWillingly shared,Conscious-levelinformationReluctantly shared,Conscious-levelinformationKnowable,Limited-conscious-level informationSubconscious-levelinformation
  80. 80. 13-82Dummy Table for American Eating HabitsAgeUse of Convenience FoodsAlwaysUseUseFrequentlyUseSometimes Rarely Use Never Use18-2425-3435-4455-6465+
  81. 81. 13-83Flowchart for Instrument Design Phase 2
  82. 82. Question Categories and StructureAdministrative Target Classification3 categories of measurement questions.1. Administrative questions identify the participant, interviewer, interviewerlocation, and conditions. These questions are rarely asked of the participantbut are necessary for studying patterns within the data and identify possibleerror sources.2. Classification questions usually cover sociological-demographic variables thatallow participants’ answers to be grouped so that patterns are revealed andcan be studied. These questions usually appear at the end of a survey.3. Target questions address the investigative questions of a specific study.These are grouped by topic in the survey. Target questions may be structuredor unstructured.
  83. 83. 13-85Engagement = Convenience“Participants are becoming more and moreaware of the value of their time. The key tomaintaining a quality dialog with them is tomake it really convenient for them toengage, whenever and wherever they want.”Tom Andersonmanaging partnerAnderson Analytics
  84. 84. 13-86Question ContentShould this question be asked?Is the question of proper scope and coverage?Can the participant adequatelyanswer this question as asked?Will the participant willinglyanswer this question as asked?
  85. 85. Criteria of Question WordingCriteriaSharedvocabulary SinglemeaningMisleadingassumptionsAdequatealternativesPersonalizedBiased1. Is the question stated in terms of a shared vocabulary?2. Does the question contain vocabulary with a single meaning?3. Does the question contain unsupported or misleadingassumptions?4. Does the question contain biased wording?5. Is the question correctly personalized?6. Are adequate alternatives presented within the question?
  86. 86. Response StrategyFactorsObjectivesof the studyParticipant’s levelof informationDegree to which participantshave thought through topicEase and clarity with whichparticipant communicatesParticipant’smotivation toshareIn choosing response options in questions, researchers must considerthese factors.
  87. 87. 13-89Free-Response Strategy - open-ended questionsWhat factors influenced your enrollment in Metro U?________________________________________________________________________________________
  88. 88. Dichotomous Response StrategyDid you attend the “A Day at College”program at Metro U?YesNoWhich one of the following factors wasmost influentialin your decision to attend Metro U?Good academic standingSpecific program of study desiredEnjoyable campus lifeMany friends from homeHigh quality of facultyMultiple Choice Response Strategy
  89. 89. Checklist Response StrategyWhich of the following factors influenced your decision to enroll in Metro U?(Check all that apply.) Tuition cost Specific program of study desired Parents’ preferences Opinion of brother or sister Many friends from home attend High quality of facultyStrongly influential Somewhat Not at allGood academic reputation   Enjoyable campus life   Many friends   High quality faculty   Semester calendar   
  90. 90. RankingPlease rank-order your top three factors from the following list based on theirinfluence in encouraging you to apply to Metro U. Use 1 to indicate the mostencouraging factor, 2 the next most encouraging factor, etc._____ Opportunity to play collegiate sports_____ Closeness to home_____ Enjoyable campus life_____ Good academic reputation_____ High quality of faculty
  91. 91. 13-93Summary of Scale TypesType Restrictions ScaleItemsData TypeRating ScalesSimple CategoryScale• Needs mutually exclusive choices One ormoreNominalMultiple ChoiceSingle-ResponseScale• Needs mutually exclusive choices• May use exhaustive list or ‘other’Many NominalMultiple ChoiceMultiple-ResponseScale(checklist)• Needs mutually exclusive choices• Needs exhaustive list or ‘other’Many NominalLikert Scale • Needs definitive positive ornegative statements with which toagree/disagreeOne ormoreOrdinalLikert-type Scale •Needs definitive positive ornegative statements with which toagree/disagreeOne ormoreOrdinal
  92. 92. 13-94Summary of Scale TypesType Restrictions Scale Items Data TypeRating ScalesNumericalScaleNeeds concepts with standardizedmeanings;Needs number anchors of the scale or end-pointsScore is a measurement of graphical spaceOne or many Ordinal orIntervalMultipleRating ListScaleNeeds words that are opposites to anchorthe end-points on the verbal scaleUp to 10 OrdinalFixed SumScaleParticipant needs ability to calculate totalto some fixed number, often 100.Two or more Interval orRatio
  93. 93. Summary of Scale TypesType Restrictions Scale Items Data TypeRating ScalesStapel Scale Needs verbal labels that areoperationally defined or standard.One or more Ordinal orIntervalGraphicRating ScaleNeeds visual images that can beinterpreted as positive or negativeanchorsScore is a measurement of graphicalspace from one anchor.One or more Ordinal(Interval, orRatio)Ranking ScalesPairedComparisonScale• Number is controlled byparticipant’s stamina and interest.Up to 10 OrdinalForcedRanking Scale• Needs mutually exclusive choices. Up to 10 Ordinal orIntervalComparativeScale• Can use verbal or graphical scale. Up to 10 Ordinal
  94. 94. Internet Survey Scale Options
  95. 95. 13-97Internet Survey Scale Options
  96. 96. 13-98Internet SurveyScale Options
  97. 97. Sources of Questions• Handbook of Marketing Scales• The Gallup Poll CumulativeIndex• Measures of Personality andSocial-Psychological Attitudes• Measures of Political Attitudes• Index to International PublicOpinion• Sourcebook of Harris NationalSurveys• Marketing Scales Handbook• American Social Attitudes DataSourcebook
  98. 98. 13-100Flowchart forInstrument DesignPhase 3
  99. 99. 13-101Guidelines for Question SequencingInteresting topics earlySimple topics earlySensitive questions laterClassification questions laterTransition between topicsReference changes limited
  100. 100. 13-102Illustrating the Funnel Approach1. How do you think this country is getting along in its relations withother countries?2. How do you think we are doing in our relations with Iran?3. Do you think we ought to be dealing with Iran differently than weare now? (If yes) What should we be doing differently?4. Some people say we should get tougher with Iran and others thinkwe are too tough as it is; how do you feel about it?
  101. 101. 13-103Branching Question
  102. 102. 13-104Components of Questionnaires
  103. 103. 13-105MindWriter Survey
  104. 104. 13-106Overcoming Instrument ProblemsBuild rapportRedesign question processExplore alternativesUse other methodsPretest
  105. 105. 13-107Key Terms• Administrative question• Branched question• Buffer question• Checklist• Classification question• Dichotomous question• Disguised question• Double-barreled question• Free-response question• Interview schedule• Leading question• Multiple-choice question• Pretesting• Primacy effect• Ranking question• Rating question• Recency effort• Screen question• Structured response• Target question– Structured– Unstructured• Unstructured response
  106. 106. Chapter 14SamplingMcGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.
  107. 107. 14-109Small Samples Can Enlighten“The proof of the pudding is in the eating.By a small sample we may judge of thewhole piece.”Miguel de Cervantes Saavedraauthor
  108. 108. 14-110PulsePoint:Research Revelation80 The average number of textmessages sent per day byAmerican teens.
  109. 109. Sampling Methods
  110. 110. 14-112The Nature of Sampling•Population•Population Element•Census•Sample•Sampling frame
  111. 111. 14-113Why Sample?GreateraccuracyAvailability ofelementsGreaterspeedSamplingprovidesLower cost
  112. 112. 14-114What Is a Sufficiently Large Sample?“In recent Gallup ‘Poll on polls,’ . . . When asked about thescientific sampling foundation on which polls are based . .. most said that a survey of 1,500 – 2,000 respondents—alarger than average sample size for national polls—cannotrepresent the views of all Americans.”Frank NewportThe Gallup Poll editor in chiefThe Gallup Organization
  113. 113. 14-115When Is a Census Appropriate?NecessaryFeasible
  114. 114. 14-116What Is a Valid Sample?Accurate Precise
  115. 115. 14-117Sampling Designwithin the Research Process
  116. 116. 14-118Types of Sampling DesignsElement Selection Probability NonprobabilityUnrestricted Simple random ConvenienceRestricted Complex random PurposiveSystematic JudgmentCluster QuotaStratified SnowballDouble
  117. 117. 14-119Steps in Sampling DesignWhat is the target population?What are the parameters of interest?What is the sampling frame?What is the appropriate samplingmethod?What size sample is needed?
  118. 118. 14-120When to Use Larger Sample?DesiredprecisionNumber ofsubgroupsConfidencelevelPopulationvarianceSmall errorrange
  119. 119. Simple RandomAdvantages• Easy to implement withrandom dialingDisadvantages• Requires list of populationelements• Time consuming• Larger sample needed• Produces larger errors• High costSystematicAdvantages• Simple to design• Easier than simple random• Easy to determine samplingdistribution of mean or proportionDisadvantages• Periodicity within populationmay skew sample and results• Trends in list may bias results• Moderate cost
  120. 120. 14-122StratifiedAdvantages• Control of sample size in strata• Increased statistical efficiency• Provides data to represent andanalyze subgroups• Enables use of differentmethods in strataDisadvantages• Increased error if subgroupsare selected at different rates• Especially expensive if strataon population must be created• High cost
  121. 121. 14-123ClusterAdvantages• Provides an unbiased estimateof population parameters ifproperly done• Economically more efficientthan simple random• Lowest cost per sample• Easy to do without listDisadvantages• Often lower statistical efficiencydue to subgroups beinghomogeneous rather thanheterogeneous• Moderate cost
  122. 122. 14-124Stratified and Cluster SamplingStratified• Population divided into fewsubgroups• Homogeneity within subgroups• Heterogeneity betweensubgroups• Choice of elements from withineach subgroupCluster• Population divided into manysubgroups• Heterogeneity within subgroups• Homogeneity betweensubgroups• Random choice of subgroups
  123. 123. 14-125Area Sampling
  124. 124. 14-126Double SamplingAdvantages• May reduce costs if first stageresults in enough data tostratify or cluster the populationDisadvantages• Increased costs ifdiscriminately used
  125. 125. 14-127Nonprobability SamplesCostFeasibilityTimeNo need togeneralizeLimited objectives
  126. 126. 14-128Nonprobability Sampling MethodsConvenienceJudgmentQuotaSnowball
  127. 127. 14-129Key Terms• Area sampling• Census• Cluster sampling• Convenience sampling• Disproportionate stratifiedsampling• Double sampling• Judgment sampling• Multiphase sampling• Nonprobability sampling• Population• Population element• Population parameters• Population proportion ofincidence• Probability sampling• Proportionate stratifiedsampling• Quota sampling• Sample statistics• Sampling• Sampling error• Sampling frame• Sequential sampling• Simple random sample• Skip interval• Snowball sampling• Stratified random sampling• Systematic sampling• Systematic variance
  128. 128. Appendix 14aDetermining SampleSizeMcGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.
  129. 129. 14-131Random Samples
  130. 130. 14-132Increasing Precision
  131. 131. 14-133Confidence Levels & the NormalCurve
  132. 132. 14-134Standard ErrorsStandard Error(Z score)% of Area ApproximateDegree ofConfidence1.00 68.27 68%1.65 90.10 90%1.96 95.00 95%3.00 99.73 99%
  133. 133. 14-135Central Limit Theorem
  134. 134. 14-136Estimates of Dining VisitsConfidence Z score % of Area Interval Range(visits per month)68% 1.00 68.27 9.48-10.5290% 1.65 90.10 9.14-10.8695% 1.96 95.00 8.98-11.0299% 3.00 99.73 8.44-11.56
  135. 135. 14-137Calculating Sample Size for Questions involvingMeansPrecisionConfidence levelSize of interval estimatePopulation DispersionNeed for FPA
  136. 136. 14-138Metro U Sample Size for MeansSteps InformationDesired confidence level 95% (z = 1.96)Size of the interval estimate  .5 meals per monthExpected range in population 0 to 30 mealsSample mean 10Standard deviation 4.1Need for finite populationadjustmentNoStandard error of the mean .5/1.96 = .255Sample size (4.1)2/ (.255)2 = 259
  137. 137. 14-139Proxies of the Population Dispersion• Previous research on the topic• Pilot test or pretest• Rule-of-thumb calculation– 1/6 of the range
  138. 138. 14-140Metro U Sample Size for ProportionsSteps InformationDesired confidence level 95% (z = 1.96)Size of the interval estimate  .10 (10%)Expected range in population 0 to 100%Sample proportion with given attribute 30%Sample dispersion Pq = .30(1-.30) = .21Finite population adjustment NoStandard error of the proportion .10/1.96 = .051Sample size .21/ (.051)2 = 81
  139. 139. 14-141Appendix 14a: Key Terms• Central limit theorem• Confidence interval• Confidence level• Interval estimate• Point estimate• Proportion
  140. 140. Addendum: KeynoteCloseUpMcGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.
  141. 141. 14-143Keynote Experiment
  142. 142. 14-144Keynote Experiment (cont.)
  143. 143. DeterminingSample SizeAppendix 14aMcGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.
  144. 144. 14-146Random Samples
  145. 145. 14-147Confidence Levels
  146. 146. 14-148Metro U. Dining Club Study

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