This project forked from commercedataservice/tutorial_311_trees_p2
Using NYC 311 data, Jonathan Auerbach and Chris Eshleman show how to use Bayesian methods to understand government service demand using storms, which serve as cleanly defined natural experiments. Part two brings together uncovers valuable insight for municipal policymakers.
Home Page: http://commercedataservice.github.io/tutorial_311_trees_p2/
##NYC 311 Data (Part 2): Modeling service requests and neighborhood characteristics
Using NYC 311 data, Jonathan Auerbach and Chris Eshleman show how to use Bayesian methods to understand government service demand using storms, which serve as cleanly defined natural experiments. Part two in a two-part brings together NYC 311 data and Census data to set the stage for powerful statistical research.
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