Abstract
There are many business questions that require the collection and analysis of qualitative data. For example, how does a visitor’s opinion of a commercial website relate to their purchases at the website? Does a positive opinion of the website, relative to a bad or mediocre opinion, lead to higher sales? This type of information is often gathered in the form of an opinion and measured as a categorical response. Also accompanying these opinions are some quantitative characteristics of the respondent; for example, their age or income. Thus, a data collection effort will include various forms of qualitative and quantitative data elements. Should we be concerned with the type of data we collect? In the prior chapters we have answered this question with a resounding yes. It is the type of the data—categorical, interval, ratio, etc.—that dictates the form of analysis that we can perform.
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Notes
- 1.
In marketing, the term demographic implies the grouping or segmentation of customers into groups with similar age, gender, family size, income, professions, education, religious affiliation, race, ethnicity, national origin, etc. The choice of the characteristics to include in a demographic is up to the decision maker.
- 2.
TiendaMía in Spanish translates to My Store in English
- 3.
The term scrubbing refers to the process of removing or changing data elements that are contaminated or incorrect, or that are in the wrong format for analysis.
- 4.
(123,000 + 48,000 + 138,000 + 94,000) / 4 = $100,750.
- 5.
Since we are working with a very small sample, the categories have been chosen to reflect differences 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.
- 6.
[number good] ÷ [number good + number bad].
- 7.
Sampling theory is a rich science that should be carefully considered prior to initiating a study.
- 8.
(0.7500 * 8 + 0.5000 * 6 + 0.6667 * 6 + 0.5556 * 9) / 29 = 0.6207.
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Guerrero, H. (2010). Analysis of Qualitative Data. In: Excel Data Analysis. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10835-8_5
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DOI: https://doi.org/10.1007/978-3-642-10835-8_5
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