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Exhibit 5.20 Extended axis field to include gender and region
So let us create categories for Age and Income that are easy 5 to work with
and simple to understand. For Age , we will use the following categories: 18–37;
38-older. Let us assume that these categories represent groups of consumers that
exhibit similar behavior: purchasing characteristics, visits to the site, level of expen-
ditures per visit, etc. For Income , we will use $0-38,000; $38,001-above. Again,
assume that we have captured similar financial behavior for respondents in these
categories. Note that we have 2 categories for each dimension and we will apply
a numeric value to the categories— 1 for values in the lowest range and 2 in the
highest. The changes resulting for the initial Table 5.2 data are shown in Table 5.6.
The conversion to these categories can be accomplished with an IF statement. For
example, IF(E3<
38000, 1,2) returns 1 if the income of the first respondent is less
than or equal to $38,000, otherwise 2 is returned.
Generally, the selection of the categories should be based on the expertise of
the data collector (TiendaMía.com) or their advisors. There are commonly accepted
=
5 Since we are working with a very small sample, the categories have been chosen to reflect differ-
ences in the relationships between demographic/financial characteristics and preferences. In other
words, I have made sure the selection of categories results in interesting findings for the purpose
of this simple example.
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