Python will be used for data wrangling, merging datasets and perform the correlation tests.

The following relationship will be tested as Subway Station level –

a.  Average of total crimes inside the station premises versus it’s Usage

b.  Correlation between the perceived safety of the station neighborhoods versus it’s Usage.

Analyze the number of crimes taken place at  the stations and in it’s vicinity. Rank the stations in descending order for the number of crimes. As second dataset, rank the the subway stations by available MIT Q Score. Use Spearman’s rank correlation between the rank values of the above two variables and assess the monotonic relationship (whether linear or not). 

Use the subway station usage information to understand the rider’s travel behavior for these stations and their perceived safety for it.