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 the cockpit and fuel tanks should be reinforced because bombers hit in those areas never made it back.
The same logic applies to books that tell the secrets of entrepreneurial success; blindly copying the advice in those books does not guarantee 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 very few, most 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 control failures.
Learn lessons from others' mistakes; sometimes the cost of your own errors can be too heavy!