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Do quantitative and qualitative data exist in isolation? The answer is a resounding
No ! Qualitative data is very often linked to quantitative data. Recall the Payment
example in Chap. 2 (see Table 2.2). Each record in the table represented an invoice
and the data ﬁelds for each transaction contained a combination of quantitative and
qualitative data; for example, \$ Amount and Account , respectively. The Account data
is associated with the \$ Amount to provide a set of circumstances and conditions (the
context) under which the quantitative value is observed. Of course, there are many
other ﬁelds in the invoice records that add context to the observation: Date Received,
Deposit, Days to Pay, and Comment .
The distinction between qualitative and quantitative is often subtle. The Comment
ﬁeld will clearly contain data that is non-quantitative, yet in some cases we can apply
simple criteria to convert non-quantitative data into a quantitative value. Suppose
the Comment ﬁeld contained customer comments that could be categorized as either
positive of negative. By counting the number in each category we have made such a
conversion, from qualitative to quantitative. We could also, for example, categorize
the number of invoices in the ranges of \$1-\$200 and >\$200 to convert quantitative
data into qualitative, or categorical, data. This is how qualitative data is dealt with
in statistics—by counting or categorizing.
The focus of Chap. 4 will be to prepare data for eventual analysis. We will do so
by utilizing the built-in data presentation and manipulation functionality of Excel.
We also will demonstrate how we apply these tools to a variety of data. Some of
these tools are available in the Data ribbon— Sort , Filter , and Validation . Others
will be found in the cell functions that Excel makes available or in non-displayed
functionality, like Fo rms . As in Chap. 3, it will be assumed that the reader has
a rudimentary understanding of data analysis, but every attempt will be made to
progress through the examples slowly and methodically, just in case those skills are
dormant.
4.2 Essentials of Effective Qualitative Data Presentation
There are numerous ways to present qualitative data stored in an Excel worksheet.
Although, for the purposes of this topic, I make a distinction between the presen-
tation and the analysis of data, this distinction is often subtle. Arguably, there is
little difference between the two, since well conceived presentation often can pro-
vide as much insight as mathematical analysis. I prefer to think of presentation as
a soft form of data analysis, but do not let the term soft imply a form of analysis
that is less valuable. These types of analyses are often just as useful as sophisticated
mathematical analyses. Additionally, soft analysis is often an initial step toward the
formal analytical tools ( hard analysis) that we will encounter in Chap. 5.
4.2.1 Planning for Data Presentation and Preparation
Before we begin our data presentation and preparation, it is essential that we plan
and organize our data collection effort. Without thoughtful planning, it is possible
to waste enormous amounts of time and energy, and to create frustration. In Chap. 2
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