Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/34112
Title: Graduate Education in Statistics and Data Science: The Why, When, Where, Who, and What
Authors: AERTS, Marc 
MOLENBERGHS, Geert 
THAS, Olivier 
Issue Date: 2021
Publisher: ANNUAL REVIEWS
Source: ANNUAL REVIEW OF STATISTICS AND ITS APPLICATION, 8 (1) , p. 25 -39
Abstract: Organizing a graduate program in statistics and data science raises many questions, offering a variety of opportunities while presenting a multitude of choices. The call for graduate programs in statistics and data science is overwhelming. How does it align with other (future) study programs at the secondary and postsecondary levels? What could or should be the natural home for data science in academia? Who meets the entry criteria, and who does not? Which strategic choices inevitably play a prominent role when developing a curriculum? We share our views on the why, when, where, who and what.
Notes: Aerts, M (corresponding author), Hasselt Univ, Interuniv Inst Biostat & Stat Bioinformat I BioSt, BE-3590 Hasselt, Belgium.
marc.aerts@uhasselt.be
Other: Aerts, M (corresponding author), Hasselt Univ, Interuniv Inst Biostat & Stat Bioinformat I BioSt, BE-3590 Hasselt, Belgium. marc.aerts@uhasselt.be
Keywords: computer science;curriculum;data science;education;graduate;interdisciplinary;statistics
Document URI: http://hdl.handle.net/1942/34112
ISSN: 2326-8298
e-ISSN: 2326-831X
DOI: 10.1146/annurev-statistics-040620-032820
ISI #: WOS:000627718500002
Rights: 2021 by Annual Reviews. All rights reserved
Category: A1
Type: Journal Contribution
Validations: ecoom 2022
Appears in Collections:Research publications

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