Survivorship bias.
During WWII, armed forces started observing survived planes. They identified the areas where bullets hit the plane the most so as to add more armour there. Thinking was that this would make planes more resistant to attacks (Shown on left hand side of image)
During WWII, armed forces started observing survived planes. They identified the areas where bullets hit the plane the most so as to add more armour there. Thinking was that this would make planes more resistant to attacks (Shown on left hand side of image)
But they only had data on the planes that survived. No one thought about the planes that didn't survive except a wise man named Abraham Wald.
He told the team to armour the areas where there weren't any bullets!!
(Shown on right hand side of above image).
He told the team to armour the areas where there weren't any bullets!!
(Shown on right hand side of above image).
His logic was that if the surviving planes are coming back with bullets in few areas, that means that those areas are adequately armoured. The areas that needed more protection were those places where there weren't any red marks(bullets).
It was highly likely that the planes that crashed and did not come back were hit in those less armoured areas.
This incident led to discovery of something called as "Survivorship bias" - tendency of people to focus on "survived data" instead of entire data.
This incident led to discovery of something called as "Survivorship bias" - tendency of people to focus on "survived data" instead of entire data.
For example, people may get enamoured seeing lot of start ups becoming Unicorns. However people are only seeing companies which have cracked the code and have become successful. Stories and data about thousands of companies which couldnt make it, doesn't get enough attention.
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