Much along the lines of the "real-life examples of common distributions" I'm interested if anyone has any pedagogical examples used to teach negative skewness?
There are plenty of canonical examples of symmetric or normal distributions used in teaching - even if ones like height and weight don't hold up under closer biological scrutiny! Maybe blood pressure is nearer normality. I like the historical example of astronomical measurement errors - it's intuitive they are no more likely to lie in one direction than another, and small errors are more likely than large.
There are also dozens of common pedagogical examples for positive skewness. People's incomes; mileage on used cars for sale; reaction times in a psychology experiment; costs of houses; number of accident claims made by an insurance customer; number of children in a family. The physical reasonableness of such examples often stems from distributions that are bounded below (usually by zero), with low values being plausible or even common, while very large (sometimes, orders of magnitude) higher values are also known to occur.
But for negative skew, clear and vivid examples do not abound, perhaps due to the lack of real-life distributions with a clear upper bound. A rather bad-taste example I was taught at school was "number of fingers". Most have ten, but it's not uncommon to lose one or more in an accident. (The upshot was that "99% of people have a higher-than-average number of fingers"!) Polydactyly rather complicates that issue, so ten is not a strict upper bound. And since both missing and extra fingers are relatively rare events, students may not have a clear intuition which of the effects predominates.
Instead, I usually use a binomial distribution with high p. But students often find "number of satisfactory components in a batch is negatively skewed" less intuitive than the complementary fact that "number of faulty components in a batch is positively skewed". (The textbook has an industrial theme; I actually use number of cracked and intact eggs in a packet of 12.) It seems students feel that "success" should be rare. Indeed some binomial cumulative probability tables require $p \leq 0.5$ so enforce this, and I've more often found students have a difficulty with questions that require them to take $p > 0.5$ than with ones which counter-intuitively require them to label contracting a terrible disease as a "success"!
Another option is to point out that if $X$ has a positively skewed distribution, then $-X$ is negatively skewed, but to attempt to place this in a practical context ("negative house prices are negatively skewed") would be doomed to pedagogical failure.
Perhaps the problem with fingers or intact eggs as examples is that they are (a) very artificial, (b) have a sharp cut-off at the mode. Good positive skew examples like incomes often have a smooth distribution, for which students have enough life-experience to be aware of the shape. Are there similar data sets, either well-known or easily grasped, which effectively illustrate negative skewness?