Centre for the Study of the Sciences and the Humanities

Numbers for policy: Practical problems in quantification

The course introduces concepts of practice and ethics of quantification, seen as an antidote to inconsiderate uses of numbers both in academia and in society.


Main content

It shows the pitfalls to be avoided and offers - with examples, tools and recipes for reasonable uses of quantitative methods. The course aims at practitioners, post-docs and PhD students with an interest in the use of evidence for policy.

The key objective is to promote skills in processing and appraising quantitative information in the context of impact assessment studies. Uncertainty appraisal and uncertainty communications are key topics.  While this is not a course on impact assessment, it gives impact assessors an extra gear, plus the set of skill needed to tell apart defensible versus indefensible assessments and risk analyses, enabling participants to spot bogus, implausible or irrelevant quantifications. Examples from epidemiology to criminology, from pharmacology to psychology, from big data to unethical use of algorithms – will be discussed. Elements of sociology of quantification will also be part of the teaching. Technical material will be presented on statistical procedures and malpractices (p-hacking, p-HARKing) and how to address them.

The course includes:

- Pedigrees for quantification such as NUSAP,

- Sensitivity auditing and ethics of quantification

The course will also include elements of  technical sensitivity analysis.


Day one, Monday 18, Morning 

9.30 – 11.00 Lesson 1. - Critical appraisal of quantitative assessments: theories and tools, Andrea Saltelli (part 1)

11.00 - 11.30 Coffee breaks

11.30 – 13.00 Lesson 2. Uncertainty and quality assurance in science for policy, Jeroen van der Sluijs (part 1)

13.00 - 14.00 Lunch

Day one, Monday 18, Afternoon

14.00 - 16.00 Practicum with Jeroen van der Sluijs

Day two, Tuesday 19, Morning

9.30 – 11.00 Lesson 3. - Critical appraisal of quantitative assessments: theories and tools, Andrea Saltelli (part 2)

11.00 - 11.30 Coffee breaks

11.30 – 13.00 Lesson 4. Uncertainty and quality assurance in science for policy, Jeroen van der Sluijs (part 2)

13.00 - 14.00 Lunch

Day two, Tuesday 19, Afternoon

14.00-16.00 Practicum with Andrea Saltelli

Day three, Wednesday 20, morning

9.30 – 11.30 Practicum with Samuele Lo Piano, hands-on practicum on sensitivity analysis.

11.30 - 12.00 Coffee breaks

12.00 – 13.30 Practicum on cases from participants  

13.30 - 14.30 Lunch

Day three, Wednesday 20, Afternoon

14.30-16.00 General discussion and lesson learned  

Support/reading material

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

This part of the course focuses on the quality of mathematical and statistical modelling, and statistical indicators as quantified evidence. These tools are of paramount importance for policy but also the most prone to abuse and misuse, as we now witness in conjunction with the ongoing reproducibility crisis. It is important to realize that, even when using statistical methods, we make normative choices, and that each model-based evidence is conditional. Uncovering these conditionalities both in terms of plain or technical assumptions and frames or metaphors is a guide to both producing and reading quantified knowledge. We critically re-examine the power and role of existing models and indicators to inform policy under conditions of uncertainty. We suggest tools for the appraisal of uncertainty, such as uncertainty and sensitivity analysis, sensitivity auditing and quantitative story-telling, and provide examples of application.

Reading material:

Uncertainty and quality assurance in science for policy, by Jeroen van der Sluijs

Science–governance interfaces are characterized by scientific controversies that employ different forms of evidence and stem from the uncertainty and plurality typical of the scientific enterprise. They are also closely interwoven with conflicting interests, values, stakes, and practices of evidence appraisal in institutions. These societal conflicts co-shape the ways in which evidence is produced, communicated and used, and how uncertainty is dealt with, while institutional settings and regulatory frameworks co-define whose evidence counts, e.g. in risk analysis, and under which conditions. The lecture will discuss a novel suite of analytical tools to map deep uncertainty, conflicts of interests, institutional practices and their interactions.

Reading material: