Date of Award


Degree Type


Degree Name

Master of Science (MS)


Mathematics and Statistics

Committee Chair(s)

Jürgen Symanzik


Christopher Corcoran


Kady Schneiter


Statistical data often have a spatial (geographic) context, be it countries of the world, states in the US, counties within a state, cities across the globe, or locations where measurements have been taken. However, most introductory statistics books do not even suggest that such data often are not independent from location, but rather are eected by some spatial association. Remedies are simple: Display data via various map views and brie y discuss which additional information can be extracted from such a graphical representation. In this report, we will visit a variety of popular introductory statistics textbooks and show how some of the data used in examples and exercises can be initially displayed via various map views, such as choropleth maps or micromaps. Students familiar with R should be able to create similar map displays by themselves via several R packages.