GIS5007 M4 Data Classification Lab

 This week we were introduced to the two different types of data used in mapping. Qualitative which which differentiates between different types of things and Quantitative helps illustrate magnitude. We then covered the different data classification methods focusing primarily on Equal Interval, Quantile, Standard Deviation, and Natural Breaks (Jenks). The advantages and disadvantages of each one were discussed and how there is no magic formula for choosing a method. During this discussion we delved into the thematic map types; Choropleth, Proportional, Isopleth/Isarithmic, and Dot. These maps differ from general reference map in that display spatial data and not just geographic features. We learned about when to use each of them and what their drawback are. Another subject we touched on was the Modifiable Areal Unit Problem (MAUP). This is a statistical bias that happens when data is aggragated. The two types of biases are zonal and scale effects. A common modern example of how this can be a problem is Gerrymandering. 

For our assignment we were asked to make two different map layout compilations.  Each one containing 4 different maps with 4 different data classification methods to illustrate how the same data is represented differently. The subject matter for our maps was the over 65 population of Miami-Dade County in Florida. The first set is percent of population over 65 and the second was a population count normalized by area. I was not expecting it to be so difficult to chose a method of data classification. There are so many factors to consider it easily becomes overwhelming. As always, we have to keep the end user in mind and even after the data classification method has been chosen we still have to achieve good map balance. Below is the original map we were provided with and the two compilation layouts I created.