The Ultimate Thematic Map -or- "Now I actually know something about proper cartography"

At last the semester's end has arrived, and all of the skills and knowledge are put to the test: The Final Project.  It looms as a daunting specter, but its creation was nothing to dread, and I rather enjoyed the challenge. The task at hand was the creation of a thematic map depicting two different data sets- mean composite SAT scores for each state and each state's percent student SAT participation.

This is my cartographic opus of the semester.  I chose to display the percent participation as a choropleth map with six classes of data, and with the data classed using the natural breaks method, which necessitated some manual adjustment.  The natural breaks classes gave the best overall view of the trend in the data; it classed values with the most similarities together, and gave the greatest difference between class members and members of other classes.  The highest value class was manually created though, as those three scores were disparate enough from the rest to warrant it.  The mean composite scores (addition of the means in Critical Reading, Math and Writing categories for each state added together to form one average score) are depicted as graduated symbols, with classification using the natural breaks method, again using manual adjustments where outliers necessitated.  

The map itself is purple for the choropleth and yellow for the graduated symbols, in order to provide the greatest amount of contrast between the two.  Gestalt principles of visual perception dictate that the thematic data stands out best when like variables are symbolized with like variables, but the like variables are different in some key respect to allow for comparison of some measure.  This means that the student participation percentage for each state is symbolized with the state's shade of purple, so that it is immediately evident that the color of the state means the same measured variable across the map, but the different shades represent different classes.  The graduated symbols follow the same principle- they are all yellow circles, but their size varies according to the class of values they represent.  This representation for the display allows for easy visual identification of the two categories of information the map is displaying- each state's mean score and percent student participation.  The colors purple and yellow are ideal for this display, as they stand out well against one another, and help increase the visual contrast of the two measures.

The interesting thing here is what happens when the above tasks are completed and the picture of the data as a whole emerges.  One can easily see that the trend is for mean composite scores to decrease with increase in student participation, and increase as participation decreases.  If the mean scores and participation percents are plotted on a graph the trend becomes very evident- which is why I included the graph at the bottom of the map.  This obviously doesn't establish a causal relationship, but surely brings up some interesting and important questions.

I remain completely astounded about how little I knew about proper methods of map-making prior to this course.  I have been employed to make maps with GIS in a few different professional positions, and am now slightly mortified to think of my outputs therein.  The upshot, though, is that I feel as though the work I've done this semester has not only been extremely personally gratifying, but also a boon to my abilities as a GIS professional.  I aim to continue my career in GIS, and can absolutely see where I will use the techniques and skills I've learned here on a regular basis.