Thinking like Bayes: how we update our beliefs when new data arrives

  Friday, July 3, 2026
This activity involved the creation of a short 3-minute video, complete with images and a script, offering a simple and reusable explanation of Bayes' theorem through an intuitive everyday example. The video clearly breaks down the core steps of Bayesian thinking: establishing our prior knowledge, observing new data, updating our beliefs, and evaluating how the final assessment changes in light of the new evidence. This animation was produced by Futurum Careers, a free online resource and magazine aimed at encouraging 14-to-19-year-olds worldwide to pursue careers in science, technology, engineering, maths and medicine (STEM), and social sciences, humanities and the arts for people and the economy (SHAPE): futurumcareers.com)

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Catia Scricciolo

Department
Economics

Goals
Rendering the scientific concept of Bayesian updating accessible by illustrating its concrete practical usefulness.
Addressees
Professionisti/Professioniste; Adolescenti; Adulti; Studenti/Studentesse; Personale non docente; Insegnanti e Personale docente
Scientific areas involved
AREA MIN. 01 - Scienze matematiche e informatiche; AREA MIN. 06 - Scienze mediche; AREA MIN. 13 - Scienze economiche e statistiche
Is part of
Noise complaints: how statistical innovations are cleaning up noisy data
Prevalent Category
Pubblicazioni (cartacee e digitali) dedicate al pubblico non accademico: Pubblicazioni (cartacee e digitali) dedicate al pubblico non accademico

Sustainable Development Goals - SDGs

Questa iniziativa contribuisce al perseguimento degli Obiettivi di Sviluppo Sostenibile dell'Agenda 2030 dell'ONU.
Maggiori informazioni su www.univr.it/sostenibilita
Industria, innovazione e infrastrutture (GOAL 9) Pace, giustizia e istituzioni forti (GOAL 16) Partnership per gli obiettivi (GOAL 17) Istruzione di qualità (GOAL 4)

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