1. © Associate Professor Dr. Jamil Bojei, 2007
MEASUREMENT
AND SCALING
Measurement and Scaling
© Associate Professor Dr. Jamil Bojei, 2007

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
© Associate Professor Dr. Jamil Bojei, 2007

3. © Associate Professor Dr. Jamil Bojei, 2007
SCALING
Measurement and Scaling
© Associate Professor Dr. Jamil Bojei, 2007

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
© Associate Professor Dr. Jamil Bojei, 2007

5. Figure 9.3 Primary Scales of Measurement
Ratio
Scale
Nominal
Scale
Ordinal
Scale
Interval
Scale
Measurement and Scaling
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6. PRIMARY SCALES OF MEASUREMENT
Nominal scales
A nominal scales uses numbers as labels or tags for identifying and classifying objects.
Measurement and Scaling
© Associate Professor Dr. Jamil Bojei, 2007

7. 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
© Associate Professor Dr. Jamil Bojei, 2007

8. 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
© Associate Professor Dr. Jamil Bojei, 2007

9. 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
© Associate Professor Dr. Jamil Bojei, 2007

10. Figure 9.4 Primary Scales of Measurement
Primary Scales Measurement
Figure 9.4 Primary Scales of Measurement
Scale
Nominal Numbers
Assigned Finish
to Runners
Ordinal Rank Order Third Second First Finish
of winners Place Place Place
Interval Performance
Rating on a
0 to 100 scale
Ratio Time to Finish,
in Seconds
Measurement and Scaling
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11. Primary scales of measurement
Basic characteristics
Common examples
Marketing 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
© Associate Professor Dr. Jamil Bojei, 2007

12. Figure 9.5 A Classification of Scaling Techniques
Noncomparative
Scales
Comparative
Scales
Itemized
Rating Scales
Continuous
Rating Scales
Paired
Comparison
Constant
Sum
Rank
Order
Likert
Stapel
Semantic
Differential
Measurement and Scaling
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13. 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
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14. 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
© Associate Professor Dr. Jamil Bojei, 2007

15. Figure 9.6 Paired Comparison Scaling
Instructions
We are going to present you with ten pairs of shampoo brands. For each pair, please
indicate which one of the two brands of shampoo in the pair you would prefer for
personal use.
Recording Form
Jhirmack
Finesse
Vidal Sassoon
Head & Shoulders
Pert
Jhirmack 1
Finesse 1A 1
Vidal Sassoon 1 1 1
Head & Shoulders
Pert 1 1 1
Number of times
preferred 3B 2 4 1
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.
Measurement and Scaling
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16. 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
© Associate Professor Dr. Jamil Bojei, 2007

17. Figure 9.7 Rank Order Scaling
Instructions
Rank 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 a
a rank of 10.
No two brands should receive the same rank number.
try to be consistent.
The criterion of preference is entirely up to you. There is no right or wrong answer. Just
Brand Rank Order
1. Crest
2. Colgate
3. Aim
4. Mentadent
5. Macleans
6. Ultra Brite
7. Close Up
8. Pepsodent
9. Plus White
10. Stripe
Measurement and Scaling
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18. 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
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19. Figure 9.8 Constant Sum Scaling
Instructions
Below 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 some
other attribute, it should receive twice as many points.
Form
AVERAGE RESPONSES OF THREE SEGMENTS
Attribute Segment I Segment II Segment III
1. Mildness
2. Lather
3. Shrinkage
4. Price
5. Fragrance
6. Packaging
7. Moisturizing
8. Cleaning Power
Sum
Measurement and Scaling
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20. 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
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21. Relative Disadvantages of Comparative Scales
Ordinal nature of the data
Inability to generalize beyond the stimulus objects scaled.
Measurement and Scaling
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22. 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
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23. Figure 10. 3 A Classification of Non Comparative Rating Scales
Continuous
Rating Scales
Itemized
Rating Scales
Semantic
Differential
Stapel
Likert
Measurement and Scaling
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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
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25. 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
Version 3
Very bad Neither good Very good
nor bad
Probably the worst I Probably the best
Measurement and Scaling
© Associate Professor Dr. Jamil Bojei, 2007

26. Table 10.1 Basic Non Comparative Scales
Measurement and Scaling
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27. 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
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28. © Associate Professor Dr. Jamil Bojei, 2007
Likert Scale
The Likert scale requires the respondents to indicate a degree of agreement or
disagreement 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 X 3 4 5
2. Sears has poor in-store service. 1 2X 3 4 5
3. I like to shop at Sears X 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
© Associate Professor Dr. Jamil Bojei, 2007

29. 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
© Associate Professor Dr. Jamil Bojei, 2007

30. Semantic Differential Scale
The 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
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31. 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
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32. © Associate Professor Dr. Jamil Bojei, 2007
Stapel Scale
The Stapel scale is a unipolar rating scale with ten categories
numbered from -5 to +5, without a neutral point (zero). This scale
is usually presented vertically.
SEARS X
HIGH QUALITY POOR SERVICE
-4X
The data obtained by using a Stapel scale can be analyzed in the
same way as semantic differential data.
Measurement and Scaling
© Associate Professor Dr. Jamil Bojei, 2007

33. Figure 10.4 Balanced and Unbalanced Scales
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
Measurement and Scaling
© Associate Professor Dr. Jamil Bojei, 2007

34. Some Unique Rating Scale Configurations
Thermometer Scale
Instructions: 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:
Like very much
Dislike very much
Measurement and Scaling
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35. Figure 10.6 Scale Evaluation
Validity
Reliability
Content
Test-Retest
Internal
Consistency
Criterion
Alternative
Forms
Construct
Convergent
Validity
Discriminant
Validity
Nomological
Validity
Measurement and Scaling
© Associate Professor Dr. Jamil Bojei, 2007

36. 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.
Measurement and Scaling
© Associate Professor Dr. Jamil Bojei, 2007