Upcoming SlideShare
×

# Abdm4064 week 07 08 measurement part 1

876 views

Published on

Data Measurement

1 Like
Statistics
Notes
• Full Name
Comment goes here.

Are you sure you want to Yes No
• Be the first to comment

Views
Total views
876
On SlideShare
0
From Embeds
0
Number of Embeds
3
Actions
Shares
0
329
0
Likes
1
Embeds 0
No embeds

No notes for slide
• This &quot;Deco&quot; border was drawn on the Slide master using PowerPoint&apos;s Rectangle and Line tools. A smaller version was placed on the Notes Master by selecting all of the elements (using Select All from the Edit menu), deselecting the unwanted elements such as the Title (holding down the Shift key and clicking on the unwanted elements), and then using Paste as Picture from the Edit menu to place the border on the Notes Master. After pasting as a picture, we used the resize handles (with Shift to maintain the proportions) to reduce it to the size you see. Be sure to delete this word processing box before using this template for your own presentation.
• Exhibit 6-1 illustrates design in the research process and highlights the topics covered by the term research design. Subsequent chapters will provide more detailed coverage of the research design topics.
• Exhibit 11-4 While Exhibit 11-3 summarized the characteristics of all the measurement scales. Exhibit 11-4, shown in the slide, illustrates the process of deciding which type of data is appropriate for one’s research needs.
• Measurement in research consists of assigning numbers to empirical events, objects or properties, or activities in compliance with a set of rules. This slide illustrates the three-part process of measurement. Text uses an example of auto show attendance. A mapping rule is a scheme for assigning numbers to aspects of an empirical event.
• Exhibit 11-1. The goal of measurement – of assigning numbers to empirical events in compliance with a set of rules – is to provide the highest-quality, lowest-error data for testing hypotheses, estimation or prediction, or description. The object of measurement is a concept, the symbols we attach to bundles of meaning that we hold and share with others. Higher-level concepts, constructs, are for specialized scientific explanatory purposes that are not directly observable and for thinking about and communicating abstractions. Concepts and constructs are used at theoretical levels while variables are used at the empirical level. Variables accept numerals or values for the purpose of testing and measurement. An operational definition defines a variable in terms of specific measurement and testing criteria. These are further reviewed in Exhibit 11-2 on page 341 of the text.
• Students will be building their measurement questions from different types of scales. They need to know the difference in order to choose the appropriate type. Each scale type has its own characteristics.
• This is a good time to ask students to develop a question they could ask that would provide only classification of the person answering it . Classification means that numbers are used to group or sort responses. Consider asking students if a number of anything is always an indication of ratio data. For example, what if we ask people how many cookies they eat a day? What if a business calls themselves the “number 1” pizza in town? These questions lead up to the next slide. Does the fact that James wears 23 mean he shoots better or plays better defense than the player donning jersey number 18? In measuring, one devises some mapping rule and then translates the observation of property indicants using this rule. Mapping rules have four characteristics and these are named in the slide. Classification means that numbers are used to group or sort responses. Order means that the numbers are ordered. One number is greater than, less than, or equal to another number. Distance means that differences between numbers can be measured. Origin means that the number series has a unique origin indicated by the number zero. Combinations of these characteristics provide four widely used classifications of measurement scales: nominal, ordinal, interval, and ratio.
• Nominal scales collect information on a variable that can be grouped into categories that are mutually exclusive and collectively exhaustive. For example, symphony patrons could be classified by whether or not they had attended prior performances. The counting of members in each group is the only possible arithmetic operation when a nominal scale is employed. If we use numerical symbols within our mapping rule to identify categories, these numbers are recognized as labels only and have no quantitative value. Nominal scales are the least powerful of the four data types. They suggest no order or distance relationship and have no arithmetic origin. The researcher is restricted to use of the mode as a measure of central tendency. The mode is the most frequently occurring value. There is no generally used measure of dispersion for nominal scales. Dispersion describes how scores cluster or scatter in a distribution. Even though LeBron James wears #23, it doesn’t mean that he is better player than #24 or a worse player than #22. The number has no meaning other than identifying James for someone who doesn’t follow the Cavs.
• Order means that the numbers are ordered. One number is greater than, less than, or equal to another number. You can ask students to develop a question that allows them to order the responses as well as group them. This is the perfect place to talk about the possible confusion that may exist when people order objects but the order may be the only consistent criteria. For instance, if two people tell them that Pizza Hut is better than Papa Johns, they are not necessarily thinking precisely the same. One could really favor Pizza Hut and never considering eating another Papa John’s pizza, which another could consider them almost interchangeable with only a slight preference for Pizza Hut. This discussion is a perfect lead in to the ever confusing ‘terror alert’ scale (shown on the next slide)…or the ‘weather warning’ system used in some states to keep drivers off the roads during poor weather. Students can probably come up with numerous other ordinal scales used in their environment.
• Ordinal data require conformity to a logical postulate, which states: If a is greater than b , and b is greater than c , then a is greater than c . Rankings are examples of ordinal scales. Attitude and preference scales are also ordinal. The appropriate measure of central tendency is the median. The median is the midpoint of a distribution. A percentile or quartile reveals the dispersion. Nonparametric tests should be used with nominal and ordinal data. This is due to their simplicity, statistical power, and lack of requirements to accept the assumptions of parametric testing.
• In measuring, one devises some mapping rule and then translates the observation of property indicants using this rule. Mapping rules have four characteristics and these are named in the slide. Classification means that numbers are used to group or sort responses. Order means that the numbers are ordered. One number is greater than, less than, or equal to another number. Distance means that differences between numbers can be measured. Origin means that the number series has a unique origin indicated by the number zero. Combinations of these characteristics provide four widely used classifications of measurement scales: nominal, ordinal, interval, and ratio.
• Researchers treat many attitude scales as interval (this will be illustrated in the next chapter). When a scale is interval and the data are relatively symmetric with one mode, one can use the arithmetic mean as the measure of central tendency. The standard deviation is the measure of dispersion. The product-moment correlation, t-tests, F-tests, and other parametric tests are the statistical procedures of choice for interval data.
• In measuring, one devises some mapping rule and then translates the observation of property indicants using this rule. Mapping rules have four characteristics and these are named in the slide. Classification means that numbers are used to group or sort responses. Order means that the numbers are ordered. One number is greater than, less than, or equal to another number. Distance means that differences between numbers can be measured. Origin means that the number series has a unique origin indicated by the number zero. Combinations of these characteristics provide four widely used classifications of measurement scales: nominal, ordinal, interval, and ratio.
• Examples Weight Height Number of children Ratio data represent the actual amounts of a variable. In business research, there are many examples such as monetary values, population counts, distances, return rates, and amounts of time. All statistical techniques mentioned up to this point are usable with ratio scales. Geometric and harmonic means are measures of central tendency and coefficients of variation may also be calculated. Higher levels of measurement generally yield more information and are appropriate for more powerful statistical procedures.
• This note relates to the effort it takes to develop a good measurement scale, and that the emphasis is always on helping the manager make a better decision—actionable data.
• Exhibit 12-1 Exhibit 12-1 illustrates where scaling fits into the research process.
• An attitude is a learned, stable predisposition to respond to oneself, other persons, objects, or issues in a consistently favorable or unfavorable way. Attitudes can be expressed or based cognitively, affectively, and behaviorally. A example for each is provided in the slide. Business researchers treat attitudes as hypothetical constructs because of their complexity and the fact that they are inferred from the measurement data, not actually observed.
• Several factors have an effect on the applicability of attitudinal research for business. Specific attitudes are better predictors of behavior than general ones. Strong attitudes are better predictors of behavior than weak attitudes composed of little intensity or topic interest. Direct experiences with the attitude object produce behavior more reliably. Cognitive-based attitudes influence behaviors better than affective-based attitudes. Affective-based attitudes are often better predictors of consumption behaviors. Using multiple measurements of attitude or several behavioral assessments across time and environments improve prediction. The influence of reference groups and the individual’s inclination to conform to these influences improves the attitude-behavior linkage.
• This note relates to the effort it takes to develop a good measurement scale, and that the emphasis is always on helping the manager make a better decision—actionable data.
• Attitude scaling is the process of assessing an attitudinal disposition using a number that represents a person’s score on an attitudinal continuum ranging from an extremely favorable disposition to an extremely unfavorable one. Scaling is the procedure for the assignment of numbers to a property of objects in order to impart some of the characteristics of numbers to the properties in question. Selecting and constructing a measurement scale requires the consideration of several factors that influence the reliability, validity, and practicality of the scale. These factors are listed in the slide. Researchers face two types of scaling objectives : 1) to measure characteristics of the participants who participate in the study, and 2) to use participants as judges of the objects or indicants presented to them. Measurement scales fall into one of four general response types : rating, ranking, categorization, and sorting. These are discussed further on the following slide. Decisions about the choice of measurement scales are often made with regard to the data properties generated by each scale: nominal, ordinal, interval, and ratio. Measurement scales are either unidimensional or multidimensional, balanced or unbalanced, forced or unforced . These characteristics are discussed further as is the issue of number of scale points and rater errors.
• A rating scale is used when participants score an object or indicant without making a direct comparison to another object or attitude. For example, they may be asked to evaluate the styling of a new car on a 7-point rating scale. Ranking scale constrain the study participant to making comparisons and determining order among two or more properties or objects. Participants may be asked to choose which one of a pair of cars has more attractive styling. A choice scale requires that participants choose one alternative over another. They could also be asked to rank-order the importance of comfort, ergonomics, performance, and price for the target vehicle. Categorization asks participants to put themselves or property indicants in groups or categories. Sorting requires that participants sort card into piles using criteria established by the researcher. The cards might contain photos or images or verbal statements of product features such as various descriptors of the car’s performance.
• With a unidimensional scale, one seeks to measure only one attribute of the participant or object. One measure of an actor’s star power is his or her ability to “carry” a movie. It is a single dimension. A multidimensional scale recognizes that an object might be better described with several dimensions. The actor’s star power variable might be better expressed by three distinct dimensions - ticket sales for the last three movies, speed of attracting financial resources, and column-inch/amount of TV coverage of the last three movies.
• A balanced rating scale has an equal number of categories above and below the midpoint. Scales can be balanced with or without a midpoint option. An unbalanced rating scale has an unequal number of favorable and unfavorable response choices.
• An unforced-choice rating scale provides participants with an opportunity to express no opinion when they are unable to make a choice among the alternatives offered. A forced-choice scale requires that participants select one of the offered alternatives.
• What is the ideal number of points for a rating scale? A scale should be appropriate for its purpose. For a scale to be useful, it should match the stimulus presented and extract information proportionate to the complexity of the attitude object, concept, or construct. E.g., A product that requires little effort or thought to purchase can be measured with a simple scale (perhaps a 3 point scale). When the product is complex, a scale with 5 to 11 points should be considered. As the number of scale points increases, the reliability of the measure increases. In some studies, scales with 11 points may produce more valid results than 3, 5, or 7 point scales. Some constructs require greater measurement sensitivity and the opportunity to extract more variance, which additional scale points provide. A larger number of scale points are needed to produce accuracy when using single-dimension versus multiple dimension scales.
• Some raters are reluctant to give extreme judgments and this fact accounts for the error of central tendency . Participants may also be “easy raters” or “hard raters” making what is called error of leniency . Suggestions for addressing these tendencies are provided in the slide.
• A primacy effect is one that occurs when respondents tend to choose the answer that they saw first. When respondents choose the answer seen most recently, the recency effect has occurred. These problems can be avoided by randomizing the order in which responses are presented.
• The halo effect is the systematic bias that the rater introduces by carrying over a generalized impression of the subject from one rating to another. For instance, a teacher may expect that a student who did well on the first exam to do well on the second. Ways of counteracting the halo effect are listed in the slide.
• This scale is also called a dichotomous scale . It offers two mutually exclusive response choices. In the example shown in the slide, the response choices are yes and no, but they could be other response choices too such as agree and disagree.
• When there are multiple options for the rater but only one answer is sought, the multiple-choice, single-response scale is appropriate. The other response may be omitted when exhaustiveness of categories is not critical or there is no possibility for an other response. This scale produces nominal data.
• This scale is a variation of the last and is called a checklist. It allows the rater to select one or several alternatives. The cumulative feature of this scale can be beneficial when a complete picture of the participant’s choice is desired, but it may also present a problem for reporting when research sponsors expect the responses to sum to 100 percent. This scale generates nominal data.
• The Likert scale was developed by Rensis Likert and is the most frequently used variation of the summated rating scale. Summated rating scales consist of statements that express either a favorable or unfavorable attitude toward the object of interest. The participant is asked to agree or disagree with each statement. Each response is given a numerical score to reflect its degree of attitudinal favorableness and the scores may be summed to measure the participant’s overall attitude. Likert-like scales may use 7 or 9 scale points. They are quick and easy to construct. The scale produces interval data. Originally, creating a Likert scale involved a procedure known as item analysis . Item analysis assesses each item based on how well it discriminates between those people whose total score is high and those whose total score is low. It involves calculating the mean scores for each scale item among the low scorers and the high scorers. The mean scores for the high-score and low-score groups are then tested for statistical significance by computing t values. After finding the t values for each statement, the statements are rank-ordered, and those statements with the highest t values are selected. Researchers have found that a larger number of items for each attitude object improves the reliability of the scale.
• From Exhibit 12-3 The semantic differential scale measures the psychological meanings of an attitude object using bipolar adjectives. Researchers use this scale for studies of brand and institutional image, employee morale, safety, financial soundness, trust, etc. The method consists of a set of bipolar rating scales, usually with 7 points, by which one or more participants rate one or more concepts on each scale item. The scale is based on the proposition that an object can have several dimensions of connotative meaning. The meanings are located in multidimensional property space, called semantic space. The semantic differential scale is efficient and easy for securing attitudes from a large sample. Attitudes may be measured in both direction and intensity. The total set of responses provides a comprehensive picture of the meaning of an object and a measure of the person doing the rating. It is standardized and produces interval data. Exhibit 12-7 provides basic instructions for constructing an SD scale.
• The steps in constructing a semantic differential scale are provided in Exhibit 12-7 .
• In Exhibit 12-8 , we see a scale used by a consulting firm to help a movie production company evaluate actors for the leading role of a risky film venture. The selection of concepts is driven by the characteristics they believe the actor must possess to produce box office financial targets. To analyze the results, the set of values for each component (evaluation, potency, and activity) is averaged.
• In Exhibit 12-9 , the data are plotted on a snake diagram. Here the adjective pairs are reordered so evaluation, potency, and activity descriptors are grouped together, with the ideal factor reflected by the left side of the scale. Profiles of the three actor candidates may be compared to each other and to the ideal.
• From Exhibit 12-3 Numerical scales have equal intervals that separate their numeric scale points. The verbal anchors serve as the labels for the extreme points. Numerical scales are often 5-point scales but may have 7 or 10 points. The participants write a number from the scale next to each item. It produces either ordinal or interval data.
• From Exhibit 12-3: A multiple rating scale is similar to the numerical scale but differs in two ways: it accepts a circled response from the rater, and the layout facilitates visualization of the results. The advantage is that a mental map of the participant’s evaluations is evident to both the rater and the researcher. This scale produces interval data.
• From Exhibit 12-3: The Stapel scale is used as an alternative to the semantic differential, especially when it is difficult to find bipolar adjectives that match the investigative question. In the example, there are three attributes of corporate image. The scale is composed of the word identifying the image dimension and a set of 10 response categories for each of the three attributes. Stapel scales produce interval data.
• From Exhibit 12-3: The constant-sum scale helps researchers to discover proportions. 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 are proportioned and summed. A participant’s ability to add may also be taxed. Its advantage is its compatibility with percent and the fact that alternatives that are perceived to be equal can be so scored. This scale produces interval data.
• From Exhibit 12-3: The graphic rating scale was originally created to enable researchers to discern fine differences. Theoretically, an infinite number of ratings is possible if participants are sophisticated enough to differentiate and record them. They are instructed to mark their response at any point along a continuum. Usually, the score is a measure of length from either endpoint. The results are treated as interval data. The difficulty is in coding and analysis. Graphic rating scales use pictures, icons, or other visuals to communicate with the rater and represent a variety of data types. Graphic scales are often used with children.
• From Exhibit 12-3: In ranking scales , the participant directly compares two or more objects and makes choices among them. The participant may be asked to select one as the best or most preferred.
• ### Abdm4064 week 07 08 measurement part 1

1. 1. Research Design :Research Design :Part 1 : MeasurementPart 1 : MeasurementResearch Design :Research Design :Part 1 : MeasurementPart 1 : MeasurementABDM4064 BUSINESS RESEARCHABDM4064 BUSINESS RESEARCHbyStephen OngPrincipal Lecturer (Specialist)Visiting Professor, Shenzhen
3. 3. MeasurementMeasurementConceptsConcepts13–3
4. 4. 13–4LEARNING OUTCOMESLEARNING OUTCOMESLEARNING OUTCOMESLEARNING OUTCOMES1. Determine what needs to be measured to addressa research question or hypothesis2. Distinguish levels of scale measurement3. Know how to form an index or composite measure4. List the three criteria for good measurement5. Perform a basic assessment of scale reliabilityand validityAfter studying this chapter, you should be able to
5. 5. 6. Describe how business researchers think ofattitudes7. Identify basic approaches to measuring attitudes8. Discuss the use of rating scales for measuringattitudes9. Represent a latent construct by constructing asummated scale10. Summarize ways to measure attitudes with rankingand sorting techniques11. Discuss major issues involved in the selection of ameasurement scale13–5LEARNING OUTCOMESLEARNING OUTCOMES(cont’d)(cont’d)LEARNING OUTCOMESLEARNING OUTCOMES(cont’d)(cont’d)
6. 6. 12. Explain the significance of decisions aboutquestionnaire design and wording13. Define alternatives for wording open-ended andfixed-alternative questions14. Summarize guidelines for questions that avoidmistakes in questionnaire design15. Describe how the proper sequence of questionsmay improve a questionnaire16. Discuss how to design a questionnaire layout17. Describe criteria for pretesting and revising aquestionnaire and for adapting it to global marketsLEARNING OUTCOMES (cont’d)LEARNING OUTCOMES (cont’d)LEARNING OUTCOMES (cont’d)LEARNING OUTCOMES (cont’d)
7. 7. 11-7FromFromInvestigativeInvestigativetotoMeasurementMeasurementQuestionsQuestions
8. 8. WHAT DO I MEASURE?WHAT DO I MEASURE? Before the measurement process can be defined,researchers have to decide exactly what it is thatneeds to be produced. The decision statement, corresponding researchquestions and research hypotheses can be used todecide what concepts need to be measured. Measurement is the process of describing someproperty of a phenomenon of interest usually byassigning numbers in a reliable and valid way. When numbers are used, the researcher must havea rule for assigning a number to an observation in away that provides an accurate description. All measurement, particularly in the social sciences,contains error.13–8
9. 9. WHAT DO I MEASURE?WHAT DO I MEASURE?(cont’d)(cont’d)ConceptsA researcher has to know what to measure beforeknowing how to measure something.A concept is a generalized idea that representssomething of meaning.Concepts such as age, sex, education and number ofchildren are relatively concrete properties and presentfew problems in either definition or measurement.Concepts such as brand loyalty, corporate culture,and so on are more abstract and are more difficult toboth define and measure.13–9
10. 10. WHAT DO I MEASURE?WHAT DO I MEASURE?(cont’d)(cont’d)Operational DefinitionsResearchers measure concepts through a processknown as operationalization, which is a process thatinvolves identifying scales that correspond to variancein the concept.Scales provide a range of values that correspond todifferent values in the concept being measured.Scales provide correspondence rules that indicatethat a certain value on a scale corresponds to sometrue value of a concept, hopefully in a truthful way.13–10
11. 11. WHAT DO I MEASURE? (cont’d)WHAT DO I MEASURE? (cont’d)Operational Definitions (cont’d)Variables Researchers use variance in concepts tomake diagnoses. Variables capture different concept values. Scales capture variance in concepts and assuch, the scales provide the researcher’svariables. For practical purposes, once a researchproject is underway, there is little differencebetween a concept and a variable.
12. 12. WHAT DO I MEASURE?WHAT DO I MEASURE?(cont’d)(cont’d)Operational Definitions (cont’d)Constructs Sometimes a single variable cannot capture aconcept alone. Using multiple variables to measure oneconcept can often provide a more completeaccount of some concept than could anysingle variable. A construct is a term used for concepts thatare measured with multiple variables. Can be very helpful in operationlizing aconcept.13–12
13. 13. EXHIBIT 13.EXHIBIT 13.33 Susceptibility to Interpersonal Influence: An Operational DefinitionSusceptibility to Interpersonal Influence: An Operational Definition
14. 14. 11-14MeasurementMeasurementSelectSelectmeasurable phenomenameasurable phenomenaDevelop a set ofDevelop a set ofmapping rulesmapping rulesApply the mapping ruleApply the mapping ruleto each phenomenonto each phenomenon
15. 15. 11-15Characteristics of MeasurementCharacteristics of Measurement
16. 16. 11-16Types of ScalesTypes of ScalesOrdinalOrdinalintervalintervalNominalNominalRatioRatio
17. 17. 11-17Levels of MeasurementLevels of MeasurementOrdinalOrdinalintervalintervalRatioRatioNominalNominalNominalNominal ClassificationClassification
18. 18. 11-18Nominal ScalesNominal ScalesMutually exclusiveMutually exclusiveandandCollectively exhaustiveCollectively exhaustivecategoriescategoriesExhibits onlyExhibits onlyclassificationclassification
19. 19. 11-19Levels of MeasurementLevels of MeasurementOrdinalOrdinalOrdinalOrdinalintervalintervalRatioRatioNominalNominal ClassificationClassificationOrderOrderClassificationClassification
20. 20. 11-20Ordinal ScalesOrdinal Scales• Characteristics ofCharacteristics ofnominal scalenominal scale• OrderOrder• Implies greater thanImplies greater thanor less thanor less than
21. 21. 11-21Levels of MeasurementLevels of MeasurementOrdinalOrdinalIntervalIntervalIntervalIntervalRatioRatioNominalNominal ClassificationClassificationOrderOrderClassificationClassificationOrderOrderClassificationClassification DistanceDistance
22. 22. 11-22Interval ScalesInterval ScalesCharacteristics ofCharacteristics ofnominal and ordinalnominal and ordinalscalesscalesEquality of interval.Equality of interval.Equal distanceEqual distancebetween numbersbetween numbers
23. 23. 11-23Levels of MeasurementLevels of MeasurementOrdinalOrdinalintervalintervalRatioRatioRatioRatioNominalNominal ClassificationClassificationOrderOrderClassificationClassificationOrderOrderClassificationClassification DistanceDistanceNatural OriginNatural OriginOrderOrderClassificationClassification DistanceDistance
24. 24. 11-24Ratio ScalesRatio ScalesCharacteristics ofCharacteristics ofnominal, ordinal,nominal, ordinal,interval scalesinterval scalesAbsolute zeroAbsolute zero
25. 25. Levels of Scale MeasurementLevels of Scale Measurement The level of scale measurement is importantbecause it determines the mathematicalcomparisons that are allowed. The four levels of scale measurement are:
26. 26. 13–26Levels of Scale MeasurementLevels of Scale Measurement(cont’d)(cont’d) Nominal Assigns a value to an object foridentification or classification purposes. Most elementary level of measurement. Ordinal Ranking scales allowing things to bearranged based on how much of someconcept they possible. Have nominal properties.
27. 27. 13–27Levels of Scale MeasurementLevels of Scale Measurement(cont’d)(cont’d) Interval Capture information about differences inquantities of a concept. Have both nominal and ordinal properties. Ratio Highest form of measurement. Have all the properties of interval scaleswith the additional attribute ofrepresenting absolute quantities. Absolute zero.
28. 28. EXHIBIT 13.EXHIBIT 13.44 Nominal, Ordinal, Interval, and Ratio Scales Provide DifferentNominal, Ordinal, Interval, and Ratio Scales Provide DifferentInformationInformation
29. 29. EXHIBIT 13.EXHIBIT 13.55 Facts About the Four Levels of ScalesFacts About the Four Levels of Scales
30. 30. 12-30Measurements are RelativeMeasurements are Relative“Any measurement must take into accountthe position of the observer. There is nosuch thing as measurement absolute, thereis only measurement relative.”Jeanette Wintersonjournalist and author
31. 31. 12-31The Scaling ProcessThe Scaling Process
32. 32. 12-32Nature of AttitudesNature of AttitudesCognitiveI think oatmeal is healthierthan corn flakes for breakfast.AffectiveBehaviouralI hate corn flakes.I intend to eat more oatmealfor breakfast.
34. 34. 12-34Measurement ScalesMeasurement Scales“All survey questions must beactionable if you want results.”Frank Schmidt, senior scientistThe Gallup Organization
35. 35. 12-35Selecting aSelecting aMeasurement ScaleMeasurement ScaleResearch objectives Response typesData propertiesNumber ofdimensionsForced or unforcedchoicesBalanced orunbalancedRater errorsNumber ofscale points
36. 36. 12-36Response TypesResponse TypesRating scaleRating scaleRanking scaleRanking scaleCategorizationCategorizationSortingSorting
37. 37. 12-37Number of DimensionsNumber of DimensionsUnidimensionalMulti-dimensional
41. 41. 12-41Rater ErrorsRater 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
42. 42. 12-42Rater ErrorsRater ErrorsPrimacy EffectRecency EffectReverse order ofalternatives periodicallyor randomly
43. 43. 12-43Rater ErrorsRater ErrorsHalo Effect• Rate one traitat a time• Reveal one traitper page• Reverse anchorsperiodically
44. 44. ATTITUDES AS HYPOTHETICALATTITUDES AS HYPOTHETICALCONSTRUCTSCONSTRUCTS Attitude An enduring disposition to consistentlyrespond in a given manner to various aspectsof the world. Components of attitudes: Affective Component The feelings or emotions toward an object Cognitive Component Knowledge and beliefs about an object Behavioural Component Predisposition to action Intentions Behavioural expectations
45. 45. Techniques for MeasuringTechniques for MeasuringAttitudesAttitudes Ranking Requiring the respondent to rank orderobjects in overall performance on thebasis of a characteristic or stimulus. Rating Asking the respondent to estimate themagnitude of a characteristic, or quality,that an object possesses by indicating ona scale where he or she would rate anobject.
46. 46. 14–46Techniques for MeasuringTechniques for MeasuringAttitudes (cont’d)Attitudes (cont’d) Sorting Presenting the respondent with severalconcepts typed on cards and requiring therespondent to arrange the cards into anumber of piles or otherwise classify theconcepts. Choice Asking a respondent to choose onealternative from among severalalternatives; it is assumed that the chosenalternative is preferred over the others.
47. 47. Attitude Rating ScalesAttitude Rating Scales Simple Attitude Scale Requires that an individual agree/disagreewith a statement or respond to a singlequestion. This type of self-rating scale classifiesrespondents into one of two categories (e.g.,yes or no). Example:THE PRESIDENT SHOULD RUN FOR RE-ELECTION_______ AGREE ______ DISAGREE
48. 48. 12-48Simple Category ScaleSimple Category ScaleI plan to purchase a MindWriter laptop in the12 months. Yes No
49. 49. Attitude Rating Scales (cont’d)Attitude Rating Scales (cont’d) Category Scale A more sensitive measure than a simplescale in that it can have more than tworesponse categories. Question construction is an extremelyimportant factor in increasing the usefulness ofthese scales. Example:How important were the following in your decision to visit San Diego? (check one for each item)VERY SOMEWHAT NOT TOOIMPORTANT IMPORTANT IMPORTANTCLIMATE ___________ ___________ ___________COST OF TRAVEL ___________ ___________ ___________FAMILY ORIENTED ___________ ___________ ___________EDUCATIONAL/HISTORICAL ASPECTS ___________ ___________ ___________FAMILIARITY WITH AREA ___________ ___________ ___________
50. 50. EXHIBIT 14.EXHIBIT 14.11 Selected Category ScalesSelected Category Scales
51. 51. 12-51Multiple-Choice,Multiple-Choice,Single-Response ScaleSingle-Response ScaleWhat newspaper do you read most often for financial news? East City Gazette West City Tribune Regional newspaper National newspaper Other (specify:_____________)
52. 52. 12-52Multiple-Choice,Multiple-Choice,Multiple-Response ScaleMultiple-Response ScaleWhat sources did you use when designing your newhome? Please check all that apply. Online planning services Magazines Independent contractor/builder Designer Architect Other (specify:_____________)
53. 53. 12-53Likert ScaleLikert ScaleThe Internet is superior to traditional libraries forcomprehensive searches. Strongly disagree Disagree Neither agree nor disagree Agree Strongly agree
54. 54. Attitude Rating Scales (cont’d)Attitude Rating Scales (cont’d) Likert Scale A popular means for measuring attitudes. Respondents indicate their own attitudesby checking how strongly they agree ordisagree with statements. Typical response alternatives: “stronglyagree,” “agree,” “uncertain,” “disagree,” and“strongly disagree.” Example:It is more fun to play a tough, competitive tennis match than toplay an easy one.___Strongly Agree ___Agree ___Not Sure ___Disagree ___Strongly Disagree
55. 55. EXHIBIT 14.EXHIBIT 14.22 Likert Scale Items for Measuring Attitudes toward Patients’Likert Scale Items for Measuring Attitudes toward Patients’Interaction with a Physician’s Service StaffInteraction with a Physician’s Service Staff
56. 56. 12-56Semantic DifferentialSemantic Differential
57. 57. 14–57Attitude Rating Scales (cont’d)Attitude Rating Scales (cont’d) Semantic Differential A series of seven-point rating scales withbipolar adjectives, such as “good” and“bad,” anchoring the ends (or poles) of thescale. A weight is assigned to each position on thescale. Traditionally, scores are 7, 6, 5, 4, 3, 2, 1,or +3, +2, +1, 0, -1, -2, -3. Example:ExcitingExciting ___ : ___ : ___ : ___ : ___ : ___ : ___ Calm___ : ___ : ___ : ___ : ___ : ___ : ___ CalmInterestingInteresting ___ : ___ : ___ : ___ : ___ : ___ : ___ Dull___ : ___ : ___ : ___ : ___ : ___ : ___ DullSimpleSimple ___ : ___ : ___ : ___ : ___ : ___ : ___ Complex___ : ___ : ___ : ___ : ___ : ___ : ___ ComplexPassivePassive ___ : ___ : ___ : ___ : ___ : ___ : ___ Active___ : ___ : ___ : ___ : ___ : ___ : ___ Active
58. 58. EXHIBIT 14.EXHIBIT 14.33 Semantic Differential Scales for Measuring Attitudes TowardSemantic Differential Scales for Measuring Attitudes TowardSupermarketsSupermarkets
59. 59. 12-59Adapting SD ScalesAdapting 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
60. 60. 12-60SD Scale for Analyzing ActorSD Scale for Analyzing ActorCandidatesCandidates
61. 61. 12-61Graphic of SD AnalysisGraphic of SD Analysis
62. 62. Other Scale Types (cont’d)Other Scale Types (cont’d) Image Profile A graphic representation of semanticdifferential data for competing brands,products, or stores to highlightcomparisons. Because the data are assumed to beinterval, either the arithmetic mean or themedian will be used to compare the profileof one product, brand, or store with that ofa competing product, brand, or store.
63. 63. EXHIBIT 14.EXHIBIT 14.44 Image Profiles of Commuter Airlines versus Major AirlinesImage Profiles of Commuter Airlines versus Major Airlines
64. 64. 12-64Numerical ScaleNumerical Scale
65. 65. Attitude Rating Scales (cont’d)Attitude Rating Scales (cont’d) Numerical Scales Scales that have numbers as responseoptions, rather than “semantic space” orverbal descriptions, to identify categories(response positions). In practice, researchers have found that a scalewith numerical labels for intermediate pointson the scale is as effective a measure as thetrue semantic differential. Example: Now that you’ve had your automobile for aboutone year, please tell us how satisfied you arewith your Ford Taurus.Extremely Dissatisfied 1 2 3 4 5 6 7 Extremely Satisfied
66. 66. 12-66Multiple Rating List ScalesMultiple Rating List Scales“Please indicate how important or unimportant each service characteristicis:”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 1
67. 67. 12-67Stapel ScalesStapel Scales
68. 68. Other Scale Types (cont’d)Other Scale Types (cont’d) Stapel Scale Uses a single adjective as a substitute forthe semantic differential when it isdifficult to create pairs of bipolaradjectives. Tends to be easier to conduct andadminister than a semantic differentialscale.
69. 69. EXHIBIT 14.EXHIBIT 14.55 A Stapel Scale for Measuring a Store’s ImageA Stapel Scale for Measuring a Store’s Image
70. 70. 12-70Constant-Sum ScalesConstant-Sum Scales
71. 71. Other Scale Types (cont’d)Other Scale Types (cont’d) Constant-Sum Scale Respondents are asked to divide a constant sumto indicate the relative importance of attributes. Respondents often sort cards, but the task may also bea rating task (e.g., indicating brand preference). Example: Divide 100 points among each of the followingbrands according to your preference for thebrand: Brand A _________ Brand B _________ Brand C _________
72. 72. 12-72Graphic Rating ScalesGraphic Rating Scales