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Measurement and Scaling
Slide 1© Associate Professor Dr. Jamil Bojei, 2007
Measurement and Scaling
Slide 2© Associate Professor Dr. Jamil Bojei, 2007
MEASUREMENT
• Measurement means assigning numbers or other symbols to characteristics of objects being measured, according to predetermined rules.
Measurement and Scaling
Slide 3© Associate Professor Dr. Jamil Bojei, 2007
SCALING
Measurement and Scaling
Slide 4© Associate Professor Dr. Jamil Bojei, 2007
SCALING
• Scaling may be considered a part of measurement. Scales place the object being measured along a continuum.
Measurement and Scaling
Slide 5© Associate Professor Dr. Jamil Bojei, 2007
Primary Scales of Measurement
Primary Scales
Nominal Scale
Ordinal Scale
RatioScale
IntervalScale
Measurement and Scaling
Slide 6© Associate Professor Dr. Jamil Bojei, 2007
PRIMARY SCALES OF MEASUREMENT
• Nominal scales A nominal scales uses numbers as labels or tags
for identifying and classifying objects.
Measurement and Scaling
Slide 7© Associate Professor Dr. Jamil Bojei, 2007
PRIMARY SCALES OF MEASUREMENT
• Ordinal scales – is a ranking scale, in an ordinal scale, numbers are assigned to objects which allows researchers to determine whether an object has more or less of a characteristics than some other object.
Measurement and Scaling
Slide 8© Associate Professor Dr. Jamil Bojei, 2007
PRIMARY SCALES OF MEASUREMENT
• Interval scale In an interval scale, numerically equal distances
on the scale represent equal values in the characteristics being measured.
Measurement and Scaling
Slide 9© Associate Professor Dr. Jamil Bojei, 2007
PRIMARY SCALES OF MEASUREMENT
• Ratio scale A ratio scales possess all the properties of the
nominal, ordinal, and interval scales. In addition, an absolute zero point is specified; that is, the origin of the scale is fixed.
Measurement and Scaling
Slide 10© Associate Professor Dr. Jamil Bojei, 2007
Primary Scales Measurement
Scale
Nominal Numbers Assigned 17 21 13 Finish to Runners
Ordinal Rank Order Third Second First Finish of winners Place Place Place
Interval Performance Rating on a 74 90 97 0 to 100 scale
Ratio Time to Finish, in Seconds 16.1 14.0 13.2
Measurement and Scaling
Slide 11© Associate Professor Dr. Jamil Bojei, 2007
Primary scales of measurementScale Basic characteristics Common
examplesMarketing examples
Permissible statistics
Nominal Numbers identify and classify objects.
Identification Card, numbering of football players.
Brands numbers, store types, sex classification
Percentages, mode
Ordinal Numbers indicate the relative positions of the objects but not the magnitude of differences between them.
Quality rankings, ranking of teams in a tournament
Preference ranking, market position, social class
Percentile, median
Interval Differences between objects can be compared; zero point is arbitrary
Temperature (Fahrenheit, Celsius)
Attitudes, opinions, index numbers
Range, mean, standard deviation
Ratio Zero point is fixed; rations of scale values can be computed
Length, weight Age, income, costs, sales, market shares.
Geometric mean (All)
Source: Maholtra, N.K. (2004) Marketing Research: An Applied Orientation. Upper-Saddle River, New Jersey, USA: Pearson Education Inc.
Measurement and Scaling
Slide 12© Associate Professor Dr. Jamil Bojei, 2007
A Classification of Scaling Techniques
ScalingTechniques
ComparativeScales
PairedComparison
ConstantSum
RankOrder
NoncomparativeScales
ItemizedRating Scales
Continuous Rating Scales
Likert
Semantic Differential
Stapel
Measurement and Scaling
Slide 13© Associate Professor Dr. Jamil Bojei, 2007
CLASSIFICATION OF SCALING TECHNIQUES
• Comparative scales – one of two types of scaling techniques in which there is direct comparison of stimulus objects with one another.
Measurement and Scaling
Slide 14© Associate Professor Dr. Jamil Bojei, 2007
CLASSIFICATION OF SCALING TECHNIQUES
• Comparative Paired comparison scaling – a respondent is
presented with a pair of alternatives and asked to select one according to some criterion
Measurement and Scaling
Slide 15© Associate Professor Dr. Jamil Bojei, 2007
Paired Comparison Scaling
InstructionsWe are going to present you with ten pairs of shampoo brands. For each pair, pleaseindicate which one of the two brands of shampoo in the pair you would prefer forpersonal use.Recording Form
A A 1 in a particular box means that the brand in that column was preferred over the brand in the corresponding row. A 0 means that the row brand was preferred over the column brand.B The number of times a brand was preferred is obtained by summing the 1s in each column.
Jhirmack
Finesse
Vidal SassoonHead & Shoulders
Pert
Number of timespreferred
Jhirmack Finesse Vidal Sassoon Head & Shoulders Pert
0
1
0
1
23B 0 4
00
0
0
1
1
1
1
1A
1
0
1
0
0
0
0
1
Measurement and Scaling
Slide 16© Associate Professor Dr. Jamil Bojei, 2007
CLASSIFICATION OF SCALING TECHNIQUES
• Comparative Rank order scaling – the respondents are
presented with several alternatives simultaneously and are asked to rank them according to some criterion.
Measurement and Scaling
Slide 17© Associate Professor Dr. Jamil Bojei, 2007
Rank Order Scaling
InstructionsRank the various brands of toothpaste in order of preference. Begin by picking out the one brand that you like most and assign it a number 1. Then find the second most preferred-brand and assign it a number 2. Continue this procedure until you have ranked all the brands of toothpaste in order of preference. The least preferred brand should be assigned aa rank of 10.
No two brands should receive the same rank number.
The criterion of preference is entirely up to you. There is no right or wrong answer. Justtry to be consistent.
Brand Rank Order 1. Crest 2. Colgate 3. Aim 4. Mentadent 5. Macleans 6. Ultra Brite 7. Close Up 8. Pepsodent 9. Plus White10. Stripe
Measurement and Scaling
Slide 18© Associate Professor Dr. Jamil Bojei, 2007
CLASSIFICATION OF SCALING TECHNIQUES
• Comparative Constant sum scaling – respondent allocate a
constant sum o units, such a points, dollars, or chips among a set of alternatives according to some specified criterion.
Measurement and Scaling
Slide 19© Associate Professor Dr. Jamil Bojei, 2007
Figure 9.8 Constant Sum Scaling
InstructionsBelow are eight attributes of bathing soaps. Please allocate 100 points among the attrib- utes so that your allocation reflects the relative importance you attach to each attribute. The more points an attribute receives, the more important the attribute is. If an attribute is not at all important, assign it zero points. If an attribute is twice as important as someother attribute, it should receive twice as many points.
Form
AVERAGE RESPONSES OF THREE SEGMENTS Attribute Segment I Segment II Segment III 1. Mildness 8 2 4 2. Lather 2 4 17 3. Shrinkage 3 9 7 4. Price 53 17 9 5. Fragrance 9 0 19 6. Packaging 7 5 9 7. Moisturizing 5 3 20 8. Cleaning Power 13 60 15 Sum 100 100 100
Measurement and Scaling
Slide 20© Associate Professor Dr. Jamil Bojei, 2007
Relative Advantages of Comparative Scales
• Small differences between stimulus objects can be detected.
• Same known reference points for all respondents.
• Easily understood and can be applied.
• Involve fewer theoretical assumptions.
• Tend to reduce halo or carryover effects from one judgment to another.
Measurement and Scaling
Slide 21© Associate Professor Dr. Jamil Bojei, 2007
Relative Disadvantages of Comparative Scales
• Ordinal nature of the data
• Inability to generalize beyond the stimulus objects scaled.
Measurement and Scaling
Slide 22© Associate Professor Dr. Jamil Bojei, 2007
CLASSIFICATION OF SCALING TECHNIQUES
• Non-comparative scales One of two types of scaling techniques in
which each stimulus objects is scaled independently of the other.
Measurement and Scaling
Slide 23© Associate Professor Dr. Jamil Bojei, 2007
A Classification of Noncomparative Rating Scales
Noncomparative Rating Scales
ContinuousRating Scales
ItemizedRating Scales
SemanticDifferential
Stapel Likert
Measurement and Scaling
Slide 24© Associate Professor Dr. Jamil Bojei, 2007
SCALING TECHNIQUES
• Non-comparative Continuous scaling – allows the respondents to
place a mark at any point along a line running between two extreme points rather than selecting from among a set o predetermined response categories.
Measurement and Scaling
Slide 25© Associate Professor Dr. Jamil Bojei, 2007
Continuous Rating Scale
Respondents rate the objects by placing a mark at the appropriate position
on a line that runs from one extreme of the criterion variable to the other.
The form of the continuous scale may vary considerably.
How would you rate Sears as a department store?
Version 1
Probably the worst - - - - - - -I - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Probably the best
Version 2
Probably the worst - - - - - - -I - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -- - Probably the best
0 10 20 30 40 50 60 70 80 90100
Version 3
Very bad Neither good Very good
nor bad
Probably the worst - - - - - - -I - - - - - - - - - - - - - - - - - - - - - -- - - - - - - - - - - - - - - - -Probably the best
0 10 20 30 40 50 60 70 80 90100
Measurement and Scaling
Slide 26© Associate Professor Dr. Jamil Bojei, 2007
TABLE 10.1 Basic Noncomparative Scales Scale Basic Characteristics Examples Advantages Disadvantages Continuous Place a mark on a Reaction to TV Easy to construct Scoring can be Rating Scale continuous line commercials cumbersome unless computerized Itemized Rating Scales Likert Scale Degree of agreement on a Measurement of Easy to construct, More time 1 (strongly disagree) to attitudes administer, and consuming 5 (strongly agree) scale understand Semantic Seven-point scale with Brand, product, and Versatile Difficult to construct Differential bipolar labels company images appropriate bipolar adjectives Stapel Scale Unipolar ten-point scale, Measurement of Easy to construct Confusing and -5 to +5, without a neutral attitudes and Administered over difficult to point (zero) images telephone apply
Measurement and Scaling
Slide 27© Associate Professor Dr. Jamil Bojei, 2007
CLASSIFICATION OF SCALING TECHNIQUES
• Non-comparative (itemised rating scales Likert – a measurement scale with five
response categories ranging from “strongly agree” to “strongly disagree”, which requires the respondent to indicate a degree of agreement or disagreement with each of series of statements related to the stimulus object.
Measurement and Scaling
Slide 28© Associate Professor Dr. Jamil Bojei, 2007
Likert ScaleThe Likert scale requires the respondents to indicate a degree of agreement ordisagreement with each of a series of statements about the stimulus objects.
Strongly Disagree Neither Agree Strongly disagree agree nor agree
disagree 1. Sears sells high quality merchandise. 1 2X 3 4 5 2. Sears has poor in-store service. 1 2X 3 4 5 3. I like to shop at Sears. 1 2 3X 4 5
• The analysis can be conducted on an item-by-item basis (profile analysis), or a total (summated) score can be calculated.
• When arriving at a total score, the categories assigned to the negative statements by the respondents should be scored by reversing the scale.
Measurement and Scaling
Slide 29© Associate Professor Dr. Jamil Bojei, 2007
CLASSIFICATION OF SCALING TECHNIQUES
• Semantic differential A seven-point rating scale with end points
associated with bipolar labels that have semantic meaning.
Measurement and Scaling
Slide 30© Associate Professor Dr. Jamil Bojei, 2007
Semantic Differential ScaleThe semantic differential is a seven-point rating scale with end
points associated with bipolar labels that have semantic meaning.
SEARS IS:
Powerful --:--:--:--:-X-:--:--: Weak
Unreliable --:--:--:--:--:-X-:--: Reliable
Modern --:--:--:--:--:--:-X-: Old-fashioned
• The negative adjective or phrase sometimes appears at the left side of the scale and sometimes at the right.
• This controls the tendency of some respondents, particularly those with very positive or very negative attitudes, to mark the right- or left-hand sides without reading the labels.
• Individual items on a semantic differential scale may be scored on either a -3 to +3 or a 1 to 7 scale.
Measurement and Scaling
Slide 31© Associate Professor Dr. Jamil Bojei, 2007
CLASSIFICATION OF SCALING TECHNIQUES
• Stapel scale A scale for measuring attitudes that consists of
a single adjective in the middle of an even-numbered ranged of values
Measurement and Scaling
Slide 32© Associate Professor Dr. Jamil Bojei, 2007
Stapel ScaleThe Stapel scale is a unipolar rating scale with ten categoriesnumbered from -5 to +5, without a neutral point (zero). This scaleis usually presented vertically.
SEARS
+5 +5+4 +4+3 +3+2 +2X+1 +1
HIGH QUALITY POOR SERVICE-1 -1-2 -2-3 -3-4X -4-5 -5
The data obtained by using a Stapel scale can be analyzed in thesame way as semantic differential data.
Measurement and Scaling
Slide 33© Associate Professor Dr. Jamil Bojei, 2007
Surfing the Internet is
____ Extremely Good
____ Very Good
____ Good
____ Bad
____ Very Bad
____ Extremely Bad
Surfing the Internet is
____ Extremely Good
____ Very Good
____ Good
____ Somewhat Good
____ Bad
____ Very Bad
Balanced Scale Unbalanced Scale
Figure 10.4 Balanced and Unbalanced Scales
Measurement and Scaling
Slide 34© Associate Professor Dr. Jamil Bojei, 2007
Thermometer ScaleInstructions: Please indicate how much you like McDonald’s hamburgers by coloring in the thermometer. Start at the bottom and color up to the temperature level that best indicates how strong your preference is. Form:
Smiling Face Scale Instructions: Please point to the face that shows how much you like the Barbie Doll. If you do not like the Barbie Doll at all, you would point to Face 1. If you liked it very much, you would point to Face 5.
Form: 1 2 3 4 5
Like very much
Dislike very much
100 75 50 25 0
Some Unique Rating Scale Configurations
Measurement and Scaling
Slide 35© Associate Professor Dr. Jamil Bojei, 2007
Figure 10.7 Scale Evaluation
Scale Evaluation
ReliabilityValidity
Test-RetestInternal
ConsistencyAlternative
Forms Construct
Criterion
Content
Convergent Validity
Discriminant Validity
NomologicalValidity
Measurement and Scaling
Slide 36© Associate Professor Dr. Jamil Bojei, 2007
Relationship Between Reliability and Validity
• If a measure is perfectly valid, it is also perfectly reliable. In this case there is no random or systematic error.
• If a measure is unreliable, it cannot be perfectly valid, since at a minimum random error is present. Thus, unreliability implies invalidity.
• If a measure is perfectly reliable, it may or may not be perfectly valid, because systematic error may still be present.
• Reliability is a necessary, but not sufficient, condition for validity.