Articles with similar analysis goals:
Wang, W. (2016) >i>Forecasting bike rental demand using New York Citi Bike data. A thesis submitted in fulfilment of the requirements for the degree of MSc. In Computing (Data Analytics) in the Dublin Institute of Technology, School of Computing College of Science of Health, 2016.
http://arrow.dit.ie/cgi/viewcontent.cgi?article=1083&context=scschcomdis

Singhvi, Divya, Somya Singhvi, Peter I. Frazier, Shane G. Henderson, Eoin O’Mahony, David B. Shmoys, and Dawn B. Woodard. ”Predicting Bike Usage for New York City’s Bike Sharing System.” Predicting Bike Usage for New York City’s Bike Sharing System (2015): 1-5. People.orie.cornell.edu. School of Operations Research and Information Engineering, Department of Computer Science. Cornell University, 2015. Ib. 25 Nov. 2016. <https://people.orie.cornell.edu/woodard/SingSingFraz15.pdf>.Copyright: Association for the Advancement of Artificial Intelligence

O’Mahony, Eoin Daniel. ”Smarter Tools For (Citi)Bike Sharing.” Diss. Cornell U, 2015. ECommons/Smarter Tools For (Citi)Bike Sharing. Cornell University, 17 Aug. 2015. Ib. 27 Nov. 2016. <http://hdl.handle.net/1813/40922>.

Vanderplas, J. (2014, June 10). Is Seattle really seeing an uptick in cycling? Retrieved November 24, 2016, from Pythonic Perambulations, https://jakevdp.github.io/blog/2014/06/10/is-seattle-really-seeing-an-uptick-in-cycling/

Deliverable: I intend to produce a statistical model which outlines which factors are the greatest determinate of Citi-bike commuter demand. Additionally, this conclusion will include a list of Census tracts which are best candidates to receive a Citi-Bike station in any future program expansion plans by the city, if commuting by Citi-bike is a policy goal.