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There are several different classification methods you can choose to organize your data when doing thematic mapping. These include equal interval, natural breaks, quantile, and standard deviation.
- Equal interval classification method—Each class has an equal range of values. That is, the difference between the high and low value is equal for each class. Use this method if your data is evenly distributed and you want to emphasize the difference in values between the features.
- Natural breaks classification method—Data values that cluster are placed into a single class. Class breaks occur where there is a gap between clusters. Use this method if your data is unevenly distributed, for example, if many features have the same or similar values, and there are gaps between groups of values.
- Quantile classification method—Each class has roughly the same number of features. If your data is evenly distributed and you want to emphasize the difference in relative position between features, you should use the quantile classification method. For example, if the point values are divided into five classes, points in the highest class would fall into the top fifth of all points.
- Standard deviation classification method—Class breaks are placed above and below the mean value at intervals of 1, 0.5, or 0.25 standard deviations, until all the data values are included in a class.