This week we examined the different classification methods for displaying geospatial data and what advantages and disadvantages come with each method.  The primary focus was on comparing the four most common data classification methods used for mapping.  The different methods are: Equal Interval, Natural Breaks, Quantile, and Standard Deviation. The underlying data centered around the percentage of African-Americans by Census Tract for Escambia County, Florida from the 2000 US Census.

The task called for creating a map with 4 individual data frames displaying the subject data using each different data classification method.  I completed the project by adding the Escambia County shapefile and copying/pasting that data frame three more times.  I then went through each  of the 4 data frames and symbolized them with a different classification method while using the same color scheme and adding all necessary map elements.  A separate map with a single method of classification was also required.  This map reflected my preferred method of data classification for the given dataset.

The examination of these data classifications should give the audience a better understanding of how the same dataset can displayed 4 ways and how each method conveys a message that is slightly different than the other.  Ultimately, the audience needs to be aware of how important it is to choose the right method for presenting data in the best possible light for the purposes of each individual map.