Defining Probabilities of Events

  • Franco OboniEmail author
  • Cesar Oboni


Probabilities measure the chance an event will occur. In risk assessments and project evaluations we are not dealing with absolute probabilities, but with relative probabilities (within a portfolio) over a specific time. Generally the time is one year and we use therefore annual probabilities. Do not confuse annual probabilities and frequencies which measure average number of occurrence over a certain time interval. The confusion comes from the fact that the number expressing probability and frequency is very similar, once it goes below say 1/10. Hence a probability of 1/10 has the same number—0.1—as a frequency of 1/10, but they do not mean at all the same conceptually.


  1. Ang A H-S, Tang WH (1975) Probability concepts in Engineering Planning and Design, Vol. I, John Wiley and sonsGoogle Scholar
  2. Carlin, BP, Louis, TA (2008). Bayesian Methods for Data Analysis (Third ed.). CRC PressGoogle Scholar
  3. NIST/SEMATECH e-Handbook of Statistical Methods, April, 2012Google Scholar
  4. Oboni C, Oboni F (2013) Factual and Foreseeable Reliability of Tailings Dams and Nuclear Reactors -a Societal Acceptability Perspective, Tailings and Mine Waste 2013, Banff, AB, November 6 to 9, 2013Google Scholar
  5. Oboni C, Oboni F (2018) Geoethical consensus building through independent risk assessments. Resources for Future Generations 2018 (RFG2018), Vancouver BC, June 16–21, 2018Google Scholar
  6. Oboni F, Oboni C (2016) The Long Shadow of Human‐Generated Geohazards: Risks and Crises, in: Geohazards Caused by Human Activity, ed. Arvin Farid, InTechOpen, ISBN 978-953-51-2802-1, Print ISBN 978-953-51-2801-4Google Scholar
  7. [Oboni et al. 2014] Oboni F, Oboni C, Caldwell J (2014) Risk assessment of the long-term performance of closed tailings, Tailings and Mine Waste 2014, Keystone CO, USA, October 5–8, 2014Google Scholar
  8. Rosenblueth E (1975) Point Estimates for Probability Moments. Proceedings of the National Academy of Sciences of the United States of America PNAS 72(10): 3812–3814CrossRefGoogle Scholar
  9. Straub D, Grêt-Regamey A (2006) A Bayesian probabilistic framework for avalanche modelling based on observations, Cold Regions Science and Technology 46: 192–203CrossRefGoogle Scholar

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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Oboni Riskope Associates Inc.RiskopeVancouverCanada

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