Consultancy Style Dissertations in Statistics and Data Science: Why and How

Serveh Sharifi Far, Vanda Inácio, Daniel Paulin, Miguel de Carvalho, Nicole H. Augustin, Mike Allerhand and Gail Robertson

The American Statistician, 2023, vol. 77, issue 3, 331-339

Abstract: In this article, we chronicle the development of the consultancy style dissertations of the MSc program in Statistics with Data Science at the University of Edinburgh. These dissertations are based on real-world data problems, in joint supervision with industrial and academic partners, and aim to get all students in the cohort together to develop consultancy skills and best practices, and also to promote their statistical leadership. Aligning with recently published research on statistical education suggesting the need for a greater focus on statistical consultancy skills, we summarize our experience in organizing and supervising such consultancy style dissertations, describe the logistics of implementing them, and review the students’ and supervisors’ feedback about these dissertations.

Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/00031305.2022.2163689 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:amstat:v:77:y:2023:i:3:p:331-339

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/UTAS20

DOI: 10.1080/00031305.2022.2163689

Access Statistics for this article

The American Statistician is currently edited by Eric Sampson

More articles in The American Statistician from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().