It’s possible the myth-writers didn’t pretend it was real, either. Ovid, for instance, might not have actually originated any of his myths, but he certainly popularized and embellished them, and (unlike Twain) he admits up front that they’re monstrous lies.
Cisco, your statistical analysis is only valid if you assume that life expectancy follows a Gaussian distribution. The mere existence of Calment is enough to prove that wrong to an extremely high degree of certainty. For a more statistical refutation, the rate of centenarians is about 1 in 3300, but the Gaussian assumption would give you a figure more like 1 in 16000.
He’s got a point though, if we can use recent history to make assumptions about the past, and I’ll grant that maybe we can’t. But you will never for one second be able to convince me that Joseph Smith and L. Ron Hubbard (for examples) were anything other that the type Der Thris is describing, and I doubt that type of person only appeared in recent times.
You probably know stats better than me, but it is my understanding that almost any data can be normalized. From there you can get the mean and standard deviation from a sample, and then you can say “Jeanne Calment is very unlikely; < 0.003 of the population” with a high confidence interval, but it would not say that she is impossible. At the same time, I’m still having a hard time understanding how a mathematical model could predict someone older than her.
Are storytellers lying? They’re certainly making stuff up – but with the intent of conveying truth through story. The same, ceteris paribus, is true for the creation and preservation fo myth and legend.
Now, if some asshat claims that the King Arthur and the Round Table cycle of legends are historically accurate, not legend embroidering on a historical base in a non-historical manner, does that invalidate them as story? That’s where I’m coming from with reference to the Bible. There’s a point to the ideals of Arthurian legend that does not depend on whether there was a historical Gawain who did such-and-such at a given time. And there need not be a historical Cain and Abel or Abraham and Isaac to have those stories convey meaningful truths about human nature. Remember how important the Exodus story was, not only to Jews remembering their heritage, but to Southern Blacks during the early days of the Civil Rights movement?
You can find a mean and a standard deviation for most distributions you’ll encounter (although, it’s worth noting that there are some perfectly valid distributions which literally don’t have either), but they’re really not all that useful for non-Gaussian distributions: The formulas you’re quoting for percentages, for instance, don’t apply.
As for statistically predicting the likelihood of someone living as old as Calment (or to some greater age), I’d take the observed likelihood of a person of age X living for one more year, and then extend that into the future. For instance, a person who reaches 100 has, by observation, somewhat over a 50% chance of reaching 101, and a person who reaches 101 has over a 50% chance of reaching 102, etc. (I don’t know the exact percentages off the top of my head, but the actuarial data exists). So I’d model the distribution of ages very old people as a power law (which falls off more slowly than a Gaussian), and go from there. Looking at it another way, very old people have a half-life of something over a year. If I were feeling really ambitious, I would go through the top ten years or so for which good statistics exist (ages 95-105, perhaps), look at the half-lives for each of those ages, and extrapolate the half-life out, too.
And that’s all I’m saying, which gets us right back to where we started: a mathematical model, as far as I know, will only tell you that it is very very unlikely that anyone has lived longer. Not that anyone has or hasn’t. Likewise, if you were unaware of Madame Calment, you could only use statistics to predict that it is very very unlikely that she existed. Turns out she did, but that’s pretty much incidental to the math.
This point got brought up by someone suggesting that a statistical model could tell you that someone has lived longer, and I don’t see how that’s possible.
This doesn’t make any sense to me. One in a million in an instant, one in a million in a year, one in a million across infinity . . . ?
Perhaps a better way of going about it as a theoretical thought experiment, but as a practical matter, cut .5 in half 22 times and she’s no less an anomaly in your model than in mine.
It’s because the distribution is not even. If you take a sample of one million people, there might be two people that achieve this feat, or there might be zero.
She’s not an anomaly at all, in my model. If we assume a falloff rate of 50% per year, and 1 in 3000 centenarians, then you would expect about 1 person in 13 billion to reach the age of 122. That’s more than the population of the world, granted, but not all that much more, such that it’s really not all that implausible that you might have one, if you were only moderately lucky. Plus, like I said, the survival rate is actually better than 50% for as far as the actuarial tables go out, and if we take a 60% survival rate for each year past 100, then you’d expect one Calmet per 230 million people, and it’s actually a bit surprising that she’s the record-holder. The best model is probably somewhere in between, which means that you should in fact expect to have about one such person.
Genesis 6:3. “And the Lord said, My spirit shall not always strive with man, for that he also is flesh: yet his days shall be an hundred and twenty years.”
I think it is more likely evoking this verse rather than anything to do with Moses.