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A map is a spatial projection of data. A map can actually be a statistical graph of its own. Single nominal variables are usually represented by different colors or symbols (geomorphological classes, types of archaeological sites, etc.). From ordinal onwards you use increasingly shaded colors or proportionally sized symbols to reflect the hierarchies in your variable. With the quantitative scales, these shades or proportions can be attributed (automatically) based on the different classes defined in your dataset. Here, you can set the amount of classes and let the values be determined based on a mean & standard deviation principle, median and quartiles, systematic intervals or a manual division. Very interesting is the statistical method of natural jenks, where you apply an algorithm that finds the largest gaps between your frequencies and builds a classification based on those. From ordinal onwards there are different possibilities to visualize the statistical properties of datasets on maps, and good examples are the displaying of bar charts or pie charts themselves on maps to compare different samples. In this way, maps become very advanced means for analysis of statistical data.

Research topics: Software & Technology