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Flickr by eden, Janine and Jim. CC BY 2.0
2012 and 2016 US Presidential election vote totals by county
Obtained from The Guardian and townhall.com via GitHub. Accessed 4/13/2017 and 6/5/2017
2013 gun ownership rates in each US state
Kalesan, Bindu, et. al. 2015. "Gun ownership and social gun culture." injuryprevention.bmj.com, June 29, 2015. Accessed 4/10/2017
2016 Socioeconomic variables
Esri Demographics. Accessed 6/16/2017
ArcGIS Living Atlas of the World. Accessed 6/16/2017
Summary of tools
This case study demonstrates a number of analytical methods that can be adapted to many different application areas, allowing you to answer a variety of questions.
Which features have the characteristics I'm interested in?
Where is the best location for a shipping distribution center, fire station, or retirement community? Which districts have more than 50,000 people and median annual incomes larger than $50,000?
Which combination of explanatory variables best predicts what I'm interested in?
What are the key variables that explain the variation in literacy rates across Africa? Which combination of variables best explains the increase in voter turnout between elections?
Where is each explanatory variable a strong (or weak) predictor of what I'm interested in?
Where are the average loan grade rankings an effective predictor of average interest rates and where are they not effective? Where are teacher-to-student ratios a good predictor of test score results?
Which explanatory variables are effective predictors of what I'm interested in?
Are average loan grade rankings an effective predictor of average interest rates? What are the key variables that explain high forest fire frequency?
In addition, working through the tutorial, you used data manipulation and management tools such as Add Field, Calculate Field, and Copy Features.