The Global Centre for Risk and Innovation (GCRI)
Risk Academy, a Nexortium programmeRisk Science and MethodsDepartment of Quantitative Risk Analysis
Rates, return periods, exceedance curves, Monte Carlo and the limits of matrices
Quantitative risk analysis turns data into probabilities with their errors attached.
risksacademy.comrisk-sciencediscipline
Twin figures for the central Apennines: L'Aquila, Amatrice and Norcia, counted from its layers at their stated dates.
For Quantitative risk analysis and statistics: the faculty's twin of L'Aquila on the planet map, the globe and in 3D. Pick a generator, switch layers, run the instruments; every layer prints its provider and date.
Drag to move, right drag or Shift with a drag to turn and tilt, Ctrl with the wheel to zoom. Keyboard: arrows move, Shift with arrows turn and tilt, + and - zoom, 0 resets, V steps through the views, Escape clears.
Flat plan of the same data: relief, the three reference epicentres with magnitude and depth, and the numbers below; the sampler's figure shows one precomputed field with its parameters. The 3D twin opens on devices with WebGL once its data and library have been checked.
The map loads from this site as it nears the view (MapLibre 6.9.1, checked by hash).
The discipline teaches probability and return periods after Cornell (1968), loss metrics such as average annual loss and exceedance probability curves, Monte Carlo simulation with its sampling error, dependence and correlation, extreme value analysis, Bayesian updating and the programming tools that apply them, on the Apennine twin's fitter, calculator and sampler, together with the limits of qualitative matrices. A graduate can fit a distribution with its standard error, build an exceedance curve by sampling and say what a risk matrix cannot tell a decision maker.
This area covers the quantitative core of risk analysis: probability and return periods, loss metrics such as average annual loss and exceedance probability curves, Monte Carlo simulation, dependence, extreme value analysis, Bayesian updating and the programming tools used to apply them, together with the limits of qualitative matrices. It is taught in the department of Quantitative Risk Analysis, Faculty of Risk Science and Methods, through 4 courses with it as primary discipline and 4 more that also teach it.
8 subtopics, taught across its courses and labs.
Not yet taught by a course: Bayesian methods for risk; Compound-event statistics.
Recent developments in quantitative risk analysis and statistics, each with its source; sources checked on 16 October 2026. Summaries are short readings of the source; follow the link for the full account.
News and research as they are published, per discipline, with the faculty's other tools.
The newest research, preprints, news and humanitarian reports for Quantitative risk analysis and statistics, each with its source and date, load here. Open the research and news hub
From the Academy's risk taxonomy: the discipline's own entries and those of its primary courses, with how many courses teach each.
No course with this primary discipline is open yet; these are planned, so you can prepare with the courses also taught here.
| Lab | What you do in it | Courses using it |
|---|---|---|
| Exposure lab | Overlay people and assets with hazard footprints | 2 |
| Trigger lab | Set forecast thresholds, pre-agreed actions and messages | 1 |
These courses count in their own primary discipline and also teach this one; they do not count towards its achievement as primary courses.
Approved for authoringno enrolment and no achievement until authored and reviewed
Cited as places where the subject is practised; the institutions named are sources here, and Risk Academy hosts every course.
Nexus Foundry system pages describe what each system and its rooms are designed to do; they are not a service on offer, and studying here gives no access to them.
Open courses in connected disciplines teach the methods this discipline will build on.