Practical Guidance for Using Monte Carlo Simulations
Abstract Number:
1111
Submission Type:
Contributed Abstract
Contributed Abstract Type:
Paper
Participants:
Richard Feinberg (1), Carolin Strobl (2)
Institutions:
(1) N/A, N/A, (2) Universität Zürich, N/A
Co-Author:
First Author:
Presenting Author:
Abstract Text:
Monte Carlo simulations have become an indispensable tool across diverse fields of research, addressing challenges such as incomplete data, small sample sizes, and ethically complex questions. Originating in the late 19th and early 20th centuries, simulations have driven groundbreaking advancements, from improving the quality of beer (arguably the first simulation by Student, 1908) to modeling nuclear warfare (von Neumann & Ulam, 1949). Today, their applications span a wide range of domains, including financial risk analysis (Benhamed & Gassouma, 2023), population genetics (Griffiths & Tavaré, 1996), and pandemic modeling (Amaro & Orce, 2022).
In this session, we will briefly explore the evolution of Monte Carlo applications and provide practical guidance on designing, conducting, and evaluating simulations. Our intent is to help attendees think through realistic considerations for their own research, such as what research questions are a good fit for this methodology, how to determine an appropriate number of replications, and how to summarize and communicate results. This presentation is based on an upcoming chapter on Monte Carlo simulations.
Keywords:
Monte Carlo|Simulations| | | |
Sponsors:
Section on Statistics and Data Science Education
Tracks:
Miscellaneous
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