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Our brain: the best event driven simulation engine

Brain & statistics

RAM analysis and, more generally, statistical methodologies are perceived to be very complex. However, we live and see “statistics” – no question about that. Every day we are obliged to make decisions and, most likely, our past experiences (probability) pave the way to an answer.

For instance, imagine you are to cross a road and stop by the pedestrian light. The light is red, though a car is fast approaching. In this specific scenario, your brain can envisage a future event of you being run over! And, of course, you decide not to cross the road. So, there is no need of a specialist to interpret life events (data) which can give insights about how to proceed or make decisions.

Pedestrian light

If you go a bit further and start analysing data, statistics can give you further insights. Let’s consider a real life example on how statistics can help the decision making process: Abraham Wald’s Work on Aircraft Survivability.

Abraham Wald was a mathematician who contributed to decision theory, geometry, and econometrics, and founded the field of statistical sequential analysis. His most famous contribution to statistics related to reviewing damaged aircrafts returning from Germany in the Second World War. The main objective of this project was to review the damage on the aircrafts and suggest areas which require more shielding.

Prior to Wald’s involvement to the project, a study had already been conducted on returning aircrafts that were damaged during battle. The conclusion of the study was to provide more armour to areas that showed extensive damage. To the contrary, Wald suggested enforcing areas with no or minimal damage. His logic was based on the idea that impairment from flak and bullets on returning aircrafts represented areas capable of enduring damage. Further analysis allowed Wald to identify similar spots on each returning aircrafts where there was no damage from enemy fire, leading Wald to conclude that these patches were the weak spots that led to the loss of a plane if hit, and must be reinforced.

There are many real life examples – you can check out another good article from WALTER HICKEY.

We, in DNV GL, have encountered this challenge of explaining statistical methods in the past. In order to overcome this, when explaining RAM and statistical analysis, we designed a document called the “Executive snack-pack”. This document includes quick videos giving general information about RAM analysis and its benefits. To download, please contact me here. Feedback will be much appreciated on the document’s content.

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