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Marketing Scales
Level of Scale
Central Tendency
 Types of Scales
Assessing Goodness of Scale
Levels of Measurement of
Scales
Nominal – scale which partitions objects
into mutually exclusive and collectively
exhaustive categories; numbers simply
used as labels; numbers used to
categorize objects.
Levels of Measurement of
Scales
Ordinal – scale in which order of objects
is known; usually rank-order scales.
Levels of Measurement of
Scales
Interval – scale in which distance
between each descriptor is known.
Levels of Measurement of
Scales
Ratio – scale in which a true zero origin
exists; the value of zero means that the
entity possesses none of the characteristic
Marketing Scales
Likert - assesses degree of
agreement/disagreement with statement.
Marketing Scales
Semantic Differential - scale anchors
are bipolar adjectives.
Marketing Scales
Graphic Rating Scale - pictures
represent descriptors.
Marketing Scales
Stapel Scale - uses range of numbers,
from –x to +x to indicate intensity of
response.
Marketing Scales
Percentage Scale - uses percentages to
indicated intensity of response.
Marketing Scales
Constant Sum Scale - respondents
need to divide numerical responses in
such a way that total score is constant
Construct (Concept)
Characteristic of an entity that varies.
Manifest – concrete (age, gender,
income)
(one indicator is usually enough to
measure the construct.)
Construct (Concept)
Characteristic of an entity that varies.
Latent - abstract concepts that you can’t easily
see (variety-seeking, intelligence)
(usually need multiple indicators to
measure the construct.)
Reliability
Degree to which measures are free
from random error and therefore yield
consistent results.
Measures of a Scale’s
Reliability
Repeatability - administer the same
scale to the same respondents at two
separate points in time.
Measures of a Scale’s
Reliability
Internal consistency - if a scale is
internally consistent, it should generate
roughly the same result by dividing the
scale into parts.
Validity
Ability of a scale to measure what
it was intended to measure.
Validity
Face (Content) Validity – degree to
which items appear to measure what
they are intended to measure.
Validity
Predictive validity – degree to which
some future event can be predicted by
a current measurement scale.
Validity
Convergent validity – degree of
association among different
measurement instruments that purport
to measure the same concept.
Validity
Discriminant validity – refers to a lack
of association among constructs that are
supposed to be different.
Validity
Concurrent validity – degree to which a
variable, measured at the same point in
time as the variable of interest, can be
predicted by the measurement instrument
If a measure is valid, it
has to lack both random
and systematic error.
Reliability is a necessary
but not sufficient
condition for validity.