Analyzing and clustering students' application preferences in higher education

DOI10.1080/02664763.2019.1709052OpenAlexW2999561307WikidataQ126356648 ScholiaQ126356648MaRDI QIDQ5861392

Zsolt T. Kosztyán, V. V. Csányi, Andras Telcs, Éva Orbán-Mihálykó, Csaba Mihálykó

Publication date: 1 March 2022

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2019.1709052

zbMATH Keywords

application preferencesimpacts of financing changeinstitutional policyinstitutional preference characteristicspreference order clustering methods

Mathematics Subject Classification ID

Applications of statistics (62Pxx)

Uses Software

• AS 136

Cites Work

• Algorithm AS 136: A K-Means Clustering Algorithm
• A generalization of the Thurstone method for multiple choice and incomplete paired comparisons
• Using gravity models for the evaluation of new university site locations: a case study
• Unbiased one-dimensional university ranking – application-based preference ordering
• The Large-Sample Distribution of the Likelihood Ratio for Testing Composite Hypotheses

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