Survivorship bias is a logical error that happens when you focus only on the winners or survivors of a process while completely ignoring the ones that failed.

This mistake creates a distorted view of reality because the missing data from the failures is invisible. It is a common type of selection bias.

Famous Example: World War II PlanesDuring World War II, the military studied returning airplanes to see where they needed extra armor.The returning planes had bullet holes mostly on the wings and tail, but very few on the engines.

Officers wanted to armor the parts with the most holes.

Statistician Abraham Wald realized this was survivorship bias.

The planes shot in the engine did not survive to come back.He advised them to armor the engines, because the planes hit there were the ones that crashed.