Cartography mapped us through a
journey of 12 modules that led to this point. For the final project module, I
created a bivariate map, where I displayed 2 thematic datasets over one
geographic area. The topic of the map was to show the SAT mean composite scores
in 2014 in each state coupled with the participation rate of each state. The
importance of creating such maps is that it shows the empirical association
between two variables. Presenting a map of the SAT scores in each state can be
deceptive in how the data is perceived. Other variables can influence why one
state has a higher performance than another state. The map that I produced will
highlight how the participation rate of persons taking the SAT exam in each
state relates to that state’s mean composite score.
To juxtapose the United States’ SAT
2014 mean composite scores next to each state’s participation rate, I chose to
display the thematic datasets as a choropleth map for representation of the SAT
mean composite scores and employed graduated symbols to signify the
participation rate in each state. For the choropleth map depicting the SAT mean composite scores, I chose a
manual 5 class data classification with a graduated color scheme of blue. For
the graduated symbols, I selected them over proportional symbols because they
are classified data whereas proportional symbols are unclassified. Since the
participation rate represented a percentage, I wanted to be able to break it
down into classes that represented the data as evenly distributed as possible. Instead
of employing 5 classes at Natural Breaks, I manually created 6 classes: 0%-10%,
11%-30%, 31%-50%, 51%-70%, 71-90%, and 91-100%. The intervals for 5 classes was
much too large. For the map layout, I chose a landscape orientation because it
is best suited for a map of the Unites States. I created 3 inset maps; an inset
map each for Alaska and Hawaii so I could zoom on the mainland at an
appropriate size without leaving Alaska and Hawaii off. For the third inset
map, I zoomed in on an area of the east coast where the states are
geographically small but they had the highest participation rate. I wanted the
map reader to be able to see that while their test scores were lower than the
national average, they also had the highest participation rate. I used Adobe
Illustrator to isolate the graduated symbols and move them around each state to
create the ideal visual hierarchy and balance. I chose a map projection of
North America Albers Equal Area Conic because equal area projections are the
ideal choice for thematic maps (Esri).
Every year, students across the country prepare for months
for SAT Exams in the hopes of getting accepted into as prestigious a university
as possible. If this map had only included the Mean SAT composite scores per
state, people would have a skewed perception of what that data truly means. By
employing a second dataset that showed the participation rate, the audience can
get a better understanding about what those scores mean. The map does a good
job depicting that while a cluster of states in the Midwest have the highest
scores, they also have the lowest participation rate.
