Sensitivity Analysis: A Practical Guide to Teaching

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Authors: S Tarantola, Ivana Aleksovska, Mariia Kozlova, Alessio Lachi, Samuele Lo Piano, Rossana Rosati, Andrea Saltelli
Cited by: 1
References: 69

Abstract

Sensitivity analysis is the process of attributing the variability of model outputs to uncertainties in input parameters and assumptions. Why is this technique important? Which methods and concepts should be prioritized in teaching it? And what instructional strategies are best suited to different audiences? This work seeks to address these questions by drawing on the experience gained from 12 summer schools conducted by the authors since 1999, along with numerous specialized training courses delivered to academia, research organizations, and international institutions. We aim to distill these experiences into practical guidance for teaching sensitivity analysis, offering both methodological foundations and pedagogical strategies to support educators and future practitioners.

Fields of Study & Subjects

Probabilistic and Robust Engineering Design Model Reduction and Neural Networks Science Education and Pedagogy

Publication details

Journal / source
Risk Analysis
Publisher
Wiley
Volume
46
Issue
5
Pages
e70242–e70242
Publication date
15 April 2026
Language
EN