Centre for the Study of the Sciences and the Humanities

Numbers for policy: Practical problems in quantification (Postponed)

The course offers examples, tools and recipes for reasonable uses of quantitative methods, and is open for project officers, analysts, practitioners, postdocs and PhD students with an interest in the use of evidence for policy.

Illustration photo with globe and numbers

Main content

PLEASE NOTE! This course is postponed to a date to be announced!.

While this is not a course on impact assessment, it gives impact assessors an extra tool: developing skills needed to tell apart defensible versus indefensible assessments and risk analyses, enabling participants to spot bogus, implausible or irrelevant quantifications. 

Technical material will be presented on statistical procedures and malpractices (p-hacking, p-HARKing) and how to address them, on pedigrees for quantification such as NUSAP,  Sensitivity auditing, quantitative story-telling and ethics of quantification. The course will mention elements of technical sensitivity analysis.


Lectures and one practicum in the morning, both days, from 9.00 - 12.30. 

Discussions in the afternoon, both days, from 14.00-16.00.


- Critical appraisal of quantitative assessments: theories and tools, Andrea Saltelli

- Uncertainty and quality assurance in science for policy, examples from the project RECIPES, Jeroen van der Sluijs

- Responsible Research and Innovation: how to quantify? Examples from the projects MAGIC and SuperMoRRI, Roger Strand.


Reading material

Saltelli, A., Benini, L., Funtowicz, S., Giampietro, M., Kaiser, M., Reinert, E. and van der Sluijs, J. P. (2020)`The technique is never neutral. How methodological choices condition the generation of narratives for sustainability.` Availiable at:  https://www.sciencedirect.com/science/article/pii/S1462901119304721

van der Sluijs, J. P. and Petersen, A. (2008) ‘Exploring the quality of evidence for complex and contested policy decisions’, Environmental Research Letters, 3(024008). Available at: http://iopscience.iop.org/article/10.1088/1748-9326/3/2/024008/meta

A. Weinberg, “Science and trans-science,” Minerva, vol. 10, pp. 209–222, 1972.

Andrea Saltelli, 2019, A short comment on statistical versus mathematical modelling, Nature Communications, 10, Article number: 3870,

Science Advice for Policy by European Academies (2019) Making sense of science for policy under conditions of complexity and uncertainty. Berlin. Available at: https://www.sapea.info/topics/making-sense-of-science/