GIS3015- Data Classification

This was a challenging week with lots of  material to cover. The objectives for week six included:

- Demonstrate four common data classification methods
- Utilize ArcGIS to prepare a map with four data frames
- Symbolize map for intuitive data acquisition
- Implement cartographic design principles to create final map
- Compare and contrast classification methods
- Identify classification best suited to represent spatial data

We used data from the 2010 Census for Escambia County and our challenge was to create four maps using the Data Classification Methods of:  Equal Interval  - Quantile - Standard Deviation - and Natural Break.

Manipulating the data by selecting the various data classification methods did in fact change, though very slightly, the results depicted in the below figure. We used the attribute field for "Percent of Population in the 2010 Census Tracts for Escambia County, Over the Age of 65." At least, I believe that is the correct LONG title. This was my personal struggle this week-- understanding and being able to conceptualize the meaning of the fields in the Attribute Table particularly:

 PCT_65ABV

Since, this was the Field we used for the Data Classification Lab. Did this mean, 65 and older or was it only above 65? And, I was not sure if the data included 100% of the population of Escambia County or was this only in reference to the 2010 Census Tract of which there were 77? (The percentages displayed on the below maps do not equal 100% - should they?) 

The Main Lesson I learned this week is: You should examine your data carefully to determine if there are natural breaks, clusters, outliers, abnormalities or inconsistencies and you should certainly know what your data is referencing or where it came from... Most of all, you should understand what the data is. In other words...Know Your Data.

I am still learning this but I have gained a much better and deeper understanding about data from completing this Lab exercise.