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Exhibit 5.19 Pivot Chart for south region only
Income and Age are a different matter. The data has been collected in increments of
$500 for income and units of years for age, resulting in many possible values for
these variables. What is the value of having such detailed information? Is it abso-
lutely necessary to have such detail for our goal of analyzing the connection between
these demographic characteristics and preferences for webpages? Can we simplify
the data by creating categories of contiguous values of the data and still answer our
questions with some level of precision?
Survey studies often group individuals into age categories spanning multiple
years (e.g. 17–21, 22–29, 30–37, etc.) that permit easier cross-tabulation analysis,
with minor loss of important detail. The same is true of income. We often find
with quantitative data that it is advantageous, from a data management point of
view, to create a limited number of categories, and this can be done after the ini-
tial collection of detailed data. Thus, the data in Table 5.2 would be collected then
conditioned or scrubbed to reflect categories for both Age and Income .Inanearlier
chapter we introduced the idea of collecting data that would serve multiple pur-
poses, and even unanticipated purposes. Table 5.2 data is a perfect example of such
data.
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