Building Resilient Statistical Communities: Promoting Statistical Literacy and Mentorship Excellence

Abstract Number:

2610 

Submission Type:

Contributed Abstract 

Contributed Abstract Type:

Speed 

Participants:

Miloni Shah (1), Anna Giczewska (2)

Institutions:

(1) Duke Clinical Research Institute, N/A, (2) N/A, N/A

Co-Author:

Anna Giczewska  
N/A

First Author:

Miloni Shah  
Duke Clinical Research Institute

Presenting Author:

Miloni Shah  
Duke Clinical Research Institute

Abstract Text:

In an era where data-driven decision-making is paramount, cultivating a robust foundation in statistical understanding is essential for statisticians entering the workforce or already established, especially in the world that emerges from the pandemic. Based on our internal experiences facilitating a peer support group we elucidate strategies employed for enhancing statistical literacy and the attributes contributing to effective communication within the statistical community. We identify the following factors that are crucial to assure success: assigning mentors, investing in continuous training and education, fostering and maintaining communication and development of quality assurance guidelines. In summary, the efforts to build resilient statistical communities contribute directly to informing policy and countering misinformation by fostering a culture of statistical literacy, data integrity, effective communication, and ethical considerations within the field of statistics. This, in turn, strengthens the foundation for evidence-based policymaking and promotes a more informed and resilient society.

Keywords:

building resilient statistical communities|mentorship excellence|statistical literacy| | |

Sponsors:

Section on Statistical Learning and Data Science

Tracks:

Miscellaneous

Can this be considered for alternate subtype?

Yes

Are you interested in volunteering to serve as a session chair?

Yes

I have read and understand that JSM participants must abide by the Participant Guidelines.

Yes

I understand that JSM participants must register and pay the appropriate registration fee by June 1, 2024. The registration fee is non-refundable.

I understand