Categorization Methods

There are five general methods of categorization of values and they will be reviewed briefly in this section: Integer mode, Categories, Boundaries, Codes, and Multiple subsets. Note that the same methods of categorization can be used to categorize cases into component graphs and to categorize cases within component graphs (e.g., in histograms or box plots).

Integer Mode. When you use Integer Mode, integer values of the selected grouping variable will be used to define the categories, and one graph will be created for all cases that belong to each category (defined by those integer values). If the selected grouping variable contains non-integer values, the software will usually truncate each encountered value of the selected grouping variable to an integer value. See also, Methods of Categorization - Integer Mode.

Categories. With this mode of categorization, you will specify the number of categories which you want to use. The software will divide the entire range of values of the selected grouping variable (from minimum to maximum) into the requested number of equal length intervals. See also, Methods of Categorization - Categories.

Boundaries. The Boundaries method will also create interval categorization, however, the intervals can be of arbitrary (e.g., uneven) width as defined by custom interval boundaries (for example, "less than -10," "greater than or equal to -10 but less than 0," "greater than or equal to 0 but less than 10," and "equal to or greater than 10"). See also, Methods of Categorization - Boundaries.

Codes. Use this method if the selected grouping variable contains "codes" (i.e., specific, meaningful values such as Male, Female) from which you want to specify the categories. See also, Methods of Categorization - Codes.

Multiple subsets. This method allows you to custom-define the categories and enables you to use more than one variable to define the category. In other words, categorizations based on multiple subset definitions of categories may not represent distributions of specific (individual) variables but distributions of frequencies of specific "events" defined by particular combinations of values of several variables (and defined by conditions which can involve any number of variables from the current data set). For example, you might specify six categories based on combinations of three variables Gender, Age, and Employment. See also, Methods of Categorization - Multiple Subsets.