Transcript Chapter Three - Brock University

Lecture 5
Measurement and Scaling:
Fundamentals and Comparative
Scaling
8-2
Measurement and Scaling
Measurement means assigning numbers or other
symbols to characteristics of objects according to
certain prespecified rules.
 One-to-one correspondence between the numbers
and the characteristics being measured.
 The rules for assigning numbers should be
standardized and applied uniformly.
 Rules must not change over objects or time.
8-3
Measurement and Scaling
Scaling involves creating a continuum upon which
measured objects are located.
Example: Consider a scale measuring attitude of
customers toward department stores. Each
respondent is assigned a number from 1 to 100, with
1 = Extremely Unfavorable, and 100 = Extremely
Favorable. Measurement is the actual assignment of
a number from 1 to 100 to each respondent. Scaling
is the process of placing the respondents on a
continuum with respect to their attitude toward
department stores.
8-4
Primary Scales of Measurement
Scale
Nominal
Ordinal
Symbols
Assigned
to Runners
Finish
B
Ratio
G
Finish
Rank Order
of Winners
3rd place
Interval
S
Performance
Rating on a
0 to 10 Scale
Time to
Finish, in
Seconds
2nd place 1st place
8.2
9.1
9.6
15.2
14.1
13.4
Primary Scales of Measurement
8-5
Nominal Scale
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The numbers serve only as labels or tags for
identifying and classifying objects.
When used for identification, there is a strict one-toone correspondence between the numbers and the
objects.
The numbers do not reflect the amount of the
characteristic possessed by the objects.
The only permissible operation on the numbers in a
nominal scale is counting.
Only a limited number of statistics, all of which are
based on frequency counts, are permissible, e.g.,
percentages, and mode.
Primary Scales of Measurement
8-6
Ordinal Scale
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A ranking scale in which numbers are assigned to
objects to indicate the relative extent to which the
objects possess some characteristic.
Can determine whether an object has more or less of
a characteristic than some other object, but not how
much more or less.
Any series of numbers can be assigned that
preserves the ordered relationships between the
objects.
In addition to the counting operation allowable for
nominal scale data, ordinal scales permit the use of
statistics based on centiles, e.g., percentile, quartile,
median.
Primary Scales of Measurement
8-7
Interval Scale
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Numerically equal distances on the scale represent
equal values in the characteristic being measured.
It permits comparison of the differences between
objects. For example, the difference between 1 and 2
is the same as between 3 and 4. The difference
between 1 and 9 (i.e., 8) is twice as large as the
difference between 2 and 4 (i.e., 2) or 6 and 8 (2).
The location of the zero point is not fixed. Both the
zero point and the units of measurem. are arbitrary.
It is NOT meaningful to take ratios of scale values
It IS meaningful to take ratios of their differences.
Statistical techniques that may be used include all of
those that can be applied to nominal and ordinal
data, and in addition the arithmetic mean, standard
deviation, correlation, and other common statistics.
Primary Scales of Measurement
8-8
Ratio Scale
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Possesses all the properties of the nominal, ordinal,
and interval scales.
It has an absolute zero point. Examples: height,
weight, age, money, sales, costs, market share,
number of customers, the rate of return.
It is meaningful to compute ratios of scale values.
For example, not only is the difference between 2
and 5 the same as the difference between 14 and 17,
but also 14 is seven times as large as 2 in an
absolute sense.
All statistical techniques can be applied to ratio data.
8-9
Illustration of Primary Scales of Measurement
Nominal
Scale
Ordinal
Scale
Interval
Scale
Ratio
Scale
No. Store
Preference
Rankings
Preference
Ratings
$ spent last
3 months
1. Lord & Taylor
2. Macy’s
3. Kmart
4. Rich’s
5. J.C. Penney
6. Neiman Marcus
7. Target
8. Saks Fifth Avenue
9. Sears
10.Wal-Mart
7
2
8
3
1
5
9
6
4
10
79
25
82
30
10
53
95
61
45
115
1-7
5
7
4
6
7
5
4
5
6
2
11-17
15
17
14
16
17
15
14
15
16
12
0
200
0
100
250
35
0
100
0
10
8-10
Primary Scales of Measurement
Scale
Nominal
Ordinal
Interval
Ratio
Basic
Characteristics
Numbers identify
& classify objects
Common
Examples
Social Security
nos., numbering
of football players
Nos. indicate the Quality rankings,
relative positions rankings of teams
of objects but not in a tournament
the magnitude of
differences
between them
Differences
Temperature
between objects (Fahrenheit)
Zero point is fixed, Length, weight
ratios of scale
values can be
compared
Marketing
Permissible Statistics
Examples
Descriptive
Inferential
Brand nos., store Percentages,
Chi-square,
types
mode
binomial test
Preference
Percentile,
rankings, market median
position, social
class
Rank-order
correlation,
Friedman
ANOVA
Attitudes,
opinions, index
Age, sales,
income, costs
Productmoment
Coefficient of
variation
Range, mean,
standard
Geometric
mean, harmonic
mean
8-11
A Classification of Scaling Techniques
Scaling Techniques
Noncomparative
Scales
Comparative
Scales
Paired
Comparison
Rank
Order
Constant
Sum
Q-Sort and
Other
Procedures
Likert
Continuous
Itemized
Rating Scales Rating Scales
Semantic
Differential
Stapel
8-12
A Comparison of Scaling Techniques
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Comparative scales involve the direct comparison
of stimulus objects. Comparative scale data must be
interpreted in relative terms and have only ordinal or
rank order properties.
In noncomparative scales, each object is scaled
independently of the others in the stimulus set. The
resulting data are generally assumed to be interval or
ratio scaled.
8-13
Relative Advantages of Comparative Scales
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Small differences between stimulus objects can be
detected (respondents are forced to choose between
two objects).
Same known reference points for all respondents.
Easily understood and can be applied easily.
Involve fewer theoretical assumptions.
Tend to reduce halo or carryover effects from one
judgment to another (e.g., comparing Pepsi vs. Coke
will not influence comparing Sprite vs. 7-up).
8-14
Relative Disadvantages of Comparative Scales
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Ordinal nature of the data: only limited number of
statistical techniques can be used
Inability to generalize beyond the objects scaled (i.e.,
if Coke and Pepsi are compared, we do not know
how Sprite would be evaluated by the respondent.
Another study is needed: Coke vs. Sprite, and Pepsi
vs. Sprite)
Comparative Scaling Techniques
8-15
Paired Comparison Scaling
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A respondent is presented with two objects and
asked to select one according to some criterion.
The data obtained are ordinal in nature.
Paired comparison scaling is the most widely used
comparative scaling technique.
With n brands, [n(n - 1) /2] paired comparisons are
required (no good when n is large)
Under the assumption of transitivity (if A is better
than B, and B is better than C, then A is better than
C), it is possible to convert paired comparison data to
a rank order.
Does not match real life well: consumers face
multiple choices rather than two at a time.
Obtaining Shampoo Preferences
Using Paired Comparisons
8-16
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 you would prefer for personal use.
Recording Form:
Jh irm a ck
Jh irm a ck
aA
F in e sse
0
a
V id a l
S a sso o n
0
Head &
S h o u ld e rs
1
P ert
0
1
0
1
1
F in e sse
1
V id a l S a sso o n
1
1
H e a d & S h o u ld e rs
0
0
0
P e rt
1
1
0
1
N u m b e r o f T im e s
b
P re fe rre d
3
2
0
4
0
0
1
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. bThe number of times a brand was preferred
is obtained by summing the 1s in each column.
8-17
Paired Comparison Selling
The most common method of taste testing is paired comparison. The
consumer is asked to sample two different products and select the one
with the most appealing taste. The test is done in private and a
minimum of 1,000 responses is considered an adequate sample. CocaCola is reported to have conducted more than 190,000 paired
comparisons before introducing New Coke.
A paired comparison
(blind) taste test
Comparative Scaling Techniques
8-18
Rank Order Scaling
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Respondents are presented with several objects
simultaneously and asked to order or rank them
according to some criterion.
It is possible that the respondent may dislike the
brand ranked 1 in an absolute sense.
Furthermore, rank order scaling also results in ordinal
data.
Only (n - 1) scaling decisions need be made in rank
order scaling.
Better resembles real life shopping (multiple choices)
Preference for Toothpaste Brands
Using 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 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. Just try to be consistent.
8-19
Preference for Toothpaste Brands
Using Rank Order Scaling
Form
Brand
Rank Order
1. Crest
_________
2. Colgate
_________
3. Aim
_________
4. Gleem
_________
5. Macleans
_________
6. Ultra Brite
_________
7. Close Up
_________
8. Pepsodent
_________
9. Plus White
_________
10. Stripe
_________
8-20
Comparative Scaling Techniques
8-21
Constant Sum Scaling
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Respondents allocate a constant sum of units, such
as 100 points to attributes of a product to reflect
their importance.
If an attribute is unimportant, the respondent assigns
it zero points.
If an attribute is twice as important as some other
attribute, it receives twice as many points.
The sum of all the points is 100. Hence, the name of
the scale.
Importance of Bathing Soap Attributes
Using a Constant Sum Scale
Instructions
On the next slide, there are eight attributes of
bathing soaps. Please allocate 100 points among
the attributes 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.
8-22
Importance of Bathing Soap Attributes
Using a Constant Sum Scale
Form
8-23
Average Responses of Three Segments
Attribute
1. Mildness
2. Bubbles
3. Shrinkage
4. Price
5. Fragrance
6. Packaging
7. Moisturizing
8. Cleaning Power
Sum
Segment I
8
2
3
53
9
7
5
13
100
Segment II
2
4
9
17
0
5
3
60
100
Segment III
4
17
7
9
19
9
20
15
100