The only tweak I'd make is really around sample sizes and statistical significance.
All success _may_ be due to luck (the error term), but we can be fairly confident (say p < .001) it isn't. Said otherwise, we can be reasonably sure that some covariates (e.g. hard work, wealth, education) are significant, given a large enough sample size and we define what qualifies as success. One of course could quibble about these - do we really have enough statistical significance for each trait? - but the fact is that every person everyday operates with some intuitive understanding that these things matter. In other words, not all outcomes are due to luck.
This is much harder to do with small sample sizes or unusual occurrences. Statistics is based on frequencies, and if we have low frequencies (such as a tech boom), we should be much less confident in the significance of each variable.
This is, presumably, why people intuitively chalk up much success during these times as survivorship bias. It's not that it certainly, absolutely is; rather, it's that we're far less confident on which variables are significant and which aren't. The error term remains.
Again, attributing it to the error term, implies mostly that we shouldn't have too much confidence in our speculations on which traits are significant during such one-off events.
The only tweak I'd make is really around sample sizes and statistical significance.
All success _may_ be due to luck (the error term), but we can be fairly confident (say p < .001) it isn't. Said otherwise, we can be reasonably sure that some covariates (e.g. hard work, wealth, education) are significant, given a large enough sample size and we define what qualifies as success. One of course could quibble about these - do we really have enough statistical significance for each trait? - but the fact is that every person everyday operates with some intuitive understanding that these things matter. In other words, not all outcomes are due to luck.
This is much harder to do with small sample sizes or unusual occurrences. Statistics is based on frequencies, and if we have low frequencies (such as a tech boom), we should be much less confident in the significance of each variable.
This is, presumably, why people intuitively chalk up much success during these times as survivorship bias. It's not that it certainly, absolutely is; rather, it's that we're far less confident on which variables are significant and which aren't. The error term remains.
Again, attributing it to the error term, implies mostly that we shouldn't have too much confidence in our speculations on which traits are significant during such one-off events.