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Re-Defining the , and of Mentoring for Professional Statisticians

Author

Listed:
  • Lauren Vollmer
  • Aparna Keshaviah
  • Dmitriy Poznyak
  • Sharon Zhao
  • Fei Xing
  • Nicholas Beyler

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.

Suggested Citation

  • Lauren Vollmer & Aparna Keshaviah & Dmitriy Poznyak & Sharon Zhao & Fei Xing & Nicholas Beyler, 2017. "Re-Defining the , and of Mentoring for Professional Statisticians," The American Statistician, Taylor & Francis Journals, vol. 71(1), pages 34-37, January.
  • Handle: RePEc:taf:amstat:v:71:y:2017:i:1:p:34-37
    DOI: 10.1080/00031305.2016.1255256
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