Preferences in college applications - a nonparametric Bayesian analysis of top-10 rankings

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Title: Preferences in college applications - a nonparametric Bayesian analysis of top-10 rankings
Authors: Ali, Alnur
Murphy, Thomas Brendan
Meila, Marina
Chen, Harr
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Date: 10-Dec-2010
Abstract: Applicants to degree courses in Irish colleges and universities rank up to ten degree courses from a list of over five hundred. These data provide a wealth of information concerning applicant degree choices. A Dirichlet process mixture of generalized Mallows models are used to explore data from a cohort of applicants. We find strong and diverse clusters, which in turn gains us important insights into the workings of the system. No previously tried models or analysis technique are able to model the data with comparable accuracy.
Funding Details: Science Foundation Ireland
Type of material: Conference Publication
Keywords: Rank Data;Clustering
Subject LCSH: Cluster analysis
College applications--Mathematical models
College choice--Mathematical models
Bayesian statistical decision theory
Language: en
Status of Item: Peer reviewed
Conference Details: NIPS Workshop on Computational Social Science and the Wisdom of Crowds, December 10th 2010, Whistler, Canada
Appears in Collections:Mathematics and Statistics Research Collection
Clique Research Collection

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