Categorical variables are those that comprise of more than one category, with no intrinsic order (Daren, 2013). From the study, the two categorical variables of interest comprised of ‘region’ and ‘type of units’. The variables are categorical because they were divided into various sub-sections. The ‘region’ variable was categorized into four groups; Northeast, Midwest, South, and West, while the ‘type of units’ variable was grouped into; Housing units, Institutional group quarters, and Non-institutional group quarters. The variables were categorized into the various sub-sections to enhance the analysis, interpretation and understanding of the data.
The researcher chose to make these variables categorical, to allow the respondents to choose the category of preference. The ‘region’ and ‘type of units’ variables are categorical variables and not continuous variables because they do not have a particular value in a given range. For the researcher to analyze data for the region, it should be coded to represent the various regions and types of units. In this study, the various regions were coded as (1=Northeast, 2=Midwest, 3=South, and 4=West). The coding allows easy analysis of this data since it does not have a particular value. For the case of the type of unit, the various categories were coded as (1=Housing unit, 2=Institutional group quarters, and 3=Non-institutional group quarters).
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The researcher used the correct explanation in presenting the two variables as categorical variables since 'region' and 'type of units' are quantitative variables. Quantitative variables refer to those that are non-numeric. Therefore, choosing region and type of units as categorical variables would be the best decision, since they do not have a numerical meaning. Therefore, for them to be analyzed, they have to be coded.
Reference
Daren S. (2013 ). The practice of statistics (2nd ed.) . New York: Freeman. ISBN 978-0-7167-4773-4.
