Survivor Bias

In statistics, there is a concept called "survivor bias," which refers to researchers focusing only on the common traits of "survivors" while ignoring the information of those who "failed."
A classic example is during World War II, when mathematician Abraham Wald was tasked with studying how to reinforce the armor of British bombers. On the returning planes, the bullet holes were mainly concentrated on the wings and tail, but Wald believed that armor should be reinforced around the cockpit and fuel tanks because bombers hit in those areas never made it back.
The same logic applies to books that tell the secrets of entrepreneurs' success; blindly copying the advice in those books does not guarantee replicating success. More valuable is analyzing the mistakes made by companies that went bankrupt.
The same is true in our circle—people always focus on the rare, sensational success stories. For example, who made millions on SHIB or NFT projects, but few analyze what went wrong with those bankrupt exchanges and funds: fraud, high leverage trading, risk management failures.
Learn lessons from others' mistakes; sometimes, the cost of your own errors can be too heavy!