Class Intervals:
- Equal ranges or intervals. The data range (difference between maximum and minimum) is calculated and divided into equal increments so that the within-class ranges are the same, such as 1-3, 4-6, 7-9, and so on.
- Equal count (quantiles). Approximately the same number of observations is put in each class. The number of classes determines the technical definition of the map (quartile if there are four classes, quintile if there are five classes, and so forth). The term quantile is the generic label for data with observations divided into equal groups. This software option gives the user the opportunity to enter the number of classes desired. (This is the default in MapInfo®.)
- Equal area. Breakpoints between classes are based on equality of area rather than equality of range or an observation count. If areas in a choropleth map vary greatly in size, this type of map will differ from an equal count map based on the same data. If areas are roughly equal in size (such as city blocks), the result will be similar to an equal count presentation.
- Natural breaks. In this approach, gaps or depressions in the frequency distribution are used to establish boundaries between classes. This is the default in ArcView®, which employs a procedure know as Jenks’ Optimization that ensures the internal homogeneity within classes while maintaining the heterogeneity among the classes. (For more details, see Dent, 1990, pp. 163-165, and Slocum, 1999, chapter 4.)
- Standard deviation (SD). SD is a statistical measure of the spread of data around the mean, or average. In the literature of stocks and mutual funds, for example, SD is often used as a risk index, since it expresses the amount of price fluctuation over time. In the context of crime, SD can be a useful way of expressing extreme values of crime occurrence or portraying various social indicators. Generally, classes are defined above and below the average in units of 1 SD. The drawback is that this method assumes an underlying normal distribution, or bell-shaped curve, something of a rarity in social data.
- Custom. As the label suggests, this option allows users to determine class intervals according to their own criteria, such as regional or national norms and thresholds determined for policy reasons.
Table 2.1 summarizes the criteria for selecting methods to define class intervals for maps, providing a guide with respect to data distribution, ease of understanding, ease of computation, and other standards. (For a comprehensive discussion of issues relating to the determination of class intervals for maps, see Slocum, 1999, chapter 4.)
