6 Finally, range-graded proportional circles limit the number of proportional circles used on a map. A dataset’s values are broken down into different ranges and a unique circle size is used to represent all data values falling within an individual range. This way, a map can be made less complex, as perhaps you have 150 data points, but only five differently sized circles on the map, with each circle representing a range of data. 31.8.2. Choropleth & Isarithmic Methods For continuous data, two mapping techniques are readily available in most GISs – choropleth and isarithmic mapping (Figure 31.6). 7 The choropleth method involves applying value or color intensity to enumeration units (census tracts, counties, states, nations) based on some statistical value. The higher an enumeration unit’s data value, the darker or more saturated the color value. Fundamental to every choropleth method are the concepts of data standardization and classification. All choropleth data must be standardized. We repeat: a choropleth map may never – ever – be used to map count data. If one maps raw data using the choropleth method, the visualization will suffer from an inherent areal bias. Not all enumeration units are the same size; thus, some enumeration units will naturally have more count data than others simply due to their areal extent. For instance, Texas and California have greater populations than Rhode Island or Connecticut. This should not be a surprise – Texas and California have huge areas compared to the other two states. If you standardize the data by area, however, Connecticut and Rhode Island are far more populated when it comes to the number of people per square kilometer. If you are interested in comparing the raw number of people living in states, you should use proportional symbols.