Things like wealth and income (and alcohol consumption) don’t even have useful mean. They’re monotonically decreasing distributions with most people scoring near 0 and a few people scoring extremely high. It’s more like an exponential distribution than a gaussian.
In the US, mean household wealth is something like 3-4x the median, and if you plug the numbers into the standard deviation formula, you’ll get something close to the mean. Even greater. Maybe that informs a very sophisticated statistician audience, but if you tell the general public ‘standard deviation,’ they think “63% of people are within that of the mean,” and that is only true of Gaussian. For exponential distribution, mean±SD gets approximately all the samples.
Standard deviation is meaningless for data sets, like wealth distribution, that are not normally distributed.
Wouldn’t it still tell you how concentrated the data are around the mean? Just not as reliably as for a gaussian distribution.
Things like wealth and income (and alcohol consumption) don’t even have useful mean. They’re monotonically decreasing distributions with most people scoring near 0 and a few people scoring extremely high. It’s more like an exponential distribution than a gaussian.
In the US, mean household wealth is something like 3-4x the median, and if you plug the numbers into the standard deviation formula, you’ll get something close to the mean. Even greater. Maybe that informs a very sophisticated statistician audience, but if you tell the general public ‘standard deviation,’ they think “63% of people are within that of the mean,” and that is only true of Gaussian. For exponential distribution, mean±SD gets approximately all the samples.
TYVM!
The fuck are you talking about? It’s still a perfectly useful statistic.
Only the sith deal in absolutes.