Easy way to defining probability of a fire in a residential area of Vancouver
Nov 4th, 2009
Easy way to defining probability
Countless times we have heard “…but we have no statistics!” or “statistics cannot be gathered for this specific topic!”, with the usual conclusion that a proper risk assessment cannot be performed because of the “lack of statistics”.
We think this is a good excuse to avoid looking at reality with a better eye, and, unfortunately the result of Statistics and Probabilities being taught usually at the same times in schools.
Probabilities and Statistics
Probabilities and statistics are two separate sciences, but people tend to forget that!
Lack of data, expensive research, inability to gather numbers etc… should never be a barrier to do a proper quantitative risk analysis, especially since such a study requires ranges of values or orders of magnitude of the probabilities, not absolute, unique “fatally wrong” numbers.
Years ago, in the Book“Improving Sustainability through Reasonable Risk & Crisis Management” (F. Oboni & C. Oboni ISBN 978-0-9784462-0-8) we introduced a methodology geared towards defining probabilities DIY based on judgemental/empirical expertise/knowledge.
The following micro-case-study will show how good guided thinking can deliver an evaluation of the range of probability of an event without using statistics. Then we will use statistics ( we purposely selected a case study where statistics do exist) to derive the “precise magic number” and compare it with the evaluation.
Why are we doing this?
Because we want to show you that Risk Based Decision Making is not only available to monster global companies, but can be used by everyone, including individuals like you and me..
Fire Hazard in Kitsilano, Vancouver
The other morning I was walking to get my coffee and saw yet another firetruck and an ambulance next to a burning house. That made me wonder what is the probability of a fire in Vancouver, actually in my neighborhood, or a square of let’s say 1km by 1km.
Using the book methodology
I have witnessed at least a serious fire every year for the last 3 years, which leads to the VH category of probabilities, but because of the wide spread fire alarm program and construction codes the houses are in a state that can be defined as G to F despite most structures are wooden and flammable materials are present.
Thus, following the Methodology the probability of occurrence of a fire in my neighborhood next year can be estimated at value between 1.5×10-1 and 2.5×10-1 (one chance in seven to one chance in four for a fire to occur).
Using National Statistics
Fire Injury per 100,000 Population in Canada in 1999 was 5.
Population in metropolitan Vancouver in 1999 was 558,138.
Metropolitan Vancouver has a surface of 114.67 km2
Population density can therefore be derived at 4870 hab/km2
We can thus compute the frequency of a fire injury per year per km2 as 0.24 in Vancouver.
I can now compute the probability of having a fire injury in my neighborhood next year ( I will not enter into the details of the calculation, as it would scare a few, but if you are interested just ask) at p=0.19 (or appx. one in five).
So, the book methodology to not only lead the right order of magnitude but a safe evaluated range of the estimation in a couple minutes of work, and with no statistics.
Needless to remind that broad estimation of the range of probabilities are what we need to perform risk assessments and support risk based decision making. Using ranges is safer than using falsely precise numbers, and estimating risks is better than walking blindly!
Tagged with: assessment, based, book, decision, making, management, risk, support, tolerability
Category: Hazard, Probabilities, Risk analysis