Re-Defining the Who, When, and Where of Mentoring for Professional Statisticians. Issue 1 (2nd January 2017)

• Record Type: Journal Article
• Authors: Vollmer, Lauren; Keshaviah, Aparna; Poznyak, Dmitriy; Zhao, Sharon; Xing, Fei; Beyler, Nicholas
• Is Part Of: American statistician. Volume 71:Issue 1(2017)
• Page Start: 34
• Page End: 37
• Publication Date: 2017-01-02
• Subjects: Informal mentoring -- Group mentoring -- Interdisciplinary mentoring; Statistics -- Periodicals; 001.42205
• DOI: 10.1080/00031305.2016.1255256
• Languages: English
• ISSNs: 0003-1305

Abstract

ABSTRACT: Organizations tailor their mentoring strategies to accommodate internal resources and preferences, producing different approaches in academic, government, and corporate environments. Across these settings, three common barriers impede effective mentoring of statisticians: overspecialization, time constraints, and geographic dispersion. The authors share mentoring strategies that have emerged at their organization, Mathematica Policy Research, to overcome these obstacles. Practices include creating a methodology working group to unite researchers with diverse backgrounds, integrating mentoring into existing workflows, and harnessing modern technological infrastructure to facilitate virtual mentoring. Although these strategies emerged within a specific professional context, they suggest opportunities for statisticians to expand the channels through which mentorship can occur.