Statistical Workshop Series

The Bootstrap and its Uses

To be held virtually via WebEx

Halverson.

Jeffrey Miecznikowski, PhD

Associate Professor

Department of Biostatistics

School of Public Health and Health Professions

University at Buffalo

Tuesday, May 5, 2020

4:00 – 6:00 PM

Online via WebEx

WebEx meeting Link

University at Buffalo

This presentation will explore the origins of the bootstrapping technique for quantifying uncertainty. Specifically, attendees will learn about the bootstrap technique for estimating the standard error and confidence intervals of functionals in a statistical model.

The bootstrapping approach and its assumptions will be compared against traditional asymptotic methods. Variations of the bootstrapping method will be examined and when each variation may be appropriately applied will be discussed. The objectives of this workshop are as follows:

1. Understand the purpose and intent of bootstrapping.

2. Identify the strengths and weaknesses of outcome measures

This workshop is free and open to all students, fellows, faculty and staff at UB and the Buffalo Translational Consortium.

WebEx Meeting Information

Tuesday, May 5, 2020 4:00 pm | 2 hours | (UTC-04:00) Eastern Time (US & Canada)

Meeting number: 470 998 046; Password: St@ts2020

 

Join by video system: Dial 470998046@ub.webex.com

You can also dial 173.243.2.68 and enter your meeting number.

 

Join by phone: +1-415-655-0001 US Toll;  Access code: 470 998 046

REGISTER FOR THIS WORKSHOP BY May 4

ACCREDITATION: The University at Buffalo Jacobs School of Medicine and Biomedical Sciences is accredited by the ACCME to provide continuing medical education for physicians.

CERTIFICATION: The University at Buffalo Jacobs School of Medicine and Biomedical Sciences designates this live activity for a maximum of 2.0 AMA PRA Category 1 Credit(s)TM.  Physicians should claim only the credit commensurate with the extent of their participation in the activity.

CREDIT: This program is supported by the National Center for Advancing Translational Sciences of the National Institutes of Health under award number UL1TR001412.