Due to the COVID-19 Pandemic, the University has instruction to cancel all in-person events through the Spring semester to adhere to city and state orders limiting public gatherings. Events still running must now take place Online— listed events will include a link in which one may access the Online webspace:

To view Mr. Bitter’s defense, enter his Online chatroom via Microsoft Team’s— it will open at 2:00 pm on Wednesday, April 22, 2020.

A Statistical Model for the Prediction of the Taxi Trip Time in the City of Chicago

Mr. Frank Bitter
University of Wisconsin-Milwaukee
MS Graduate Student – Teaching Assistant

“This thesis addresses the problem of prediction of taxi trip duration for any given day, time, pickup point and dropoff point. Data on taxi trips from the Chicago Data Portal is used. The main idea of the model is to cluster similar trips together and use the mean duration of all those clustered taxi trips to predict the duration of a new taxi trip in that cluster. Furthermore, for a possible additional reduction of prediction error, estimators from different days which are not significantly different from each other are pooled together. It is shown that this procedure improves prediction error.”

Committee Members:
Profs. Daniel Gervini (Advisor); Peter Hinow & David Spade

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