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#1




New Research Claims Jeanne Calment, thought to be worlds longest living human at 122, a fraud.
https://www.insideedition.com/didwo...identity49648
I downloaded the relevant research article and it seems to give a lot in the way of speculation, but I have always had problems with this claim because it seems incredible that mathematically she could live to age 122 when the next oldest died at 119. 
#2




It's pretty funny when you think about it. If true, I doubt she was remotely thinking about "stealing" the record as the world's oldest person when she assumed her mother's identity, she was just evading taxes. She surely wouldn't have considered the possibility that she'd live to 99, and what might ensue. Did she deliberately seek to draw attention to her apparent age? Perhaps she was trapped in the lie when it started to attract attention.

#3




Here is the link to the site from which you may download the PDF if interested:
https://www.researchgate.net/publica...t_of_longevity The photographs are especially compelling. 
#4




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When she turned 110 and was in a nursing home some minor publicity was had. Only when the century of the Van Gogh visit came in 1988, and Van Gogh had visited her "husband's" store did the press interview her and she became world famous. One fact that stands out to me is that no other person aged 110 or older has been seen to walk or sit upright. She did both until her late 100teens. 


#5




I'll be dipped.
Since the 2nd oldest record is 119, it isn't a huge drop. But still.
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Sometimes I doubt your commitment to sparkle motion 
#6




Wouldn't be the first time it would have happened. This listing of revoked longevity claims includes no fewer than three people at one time recognized by Guinness as the world's oldest person (Joubert, Williams, and Izumi).

#7




She smoked and drank booze every day. I want to believe.

#8




I'm suspect of Sarah Knauss' claim for the same reason:
https://en.wikipedia.org/wiki/List_o..._oldest_people If you look at this list, you would expect the distribution you see from #3#100. It seems incredible that Knauss and Calment would be such extreme outliers from the curve. 
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#10




It's very telling that all the debunked claims were by claimed Confederate soldiers. Albert Woolson, the last Union veteran, died in 1956 and is undisputed. Not only is there a lot of "Lost Cause" oneupmanship, but a lot of Confederate records were destroyed by the end of the war (making claims a lot harder to disprove).

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Sometimes I doubt your commitment to sparkle motion Last edited by Wesley Clark; 01012019 at 08:22 PM. 
#12




#13




Hijack: there was an item in the paper yesterday that the last WWII vet had died. At 112. This means he was born in 1906, just like my father. What is astonishing is that that means that he was 35 in 1941. Weren't there any who turned 18, say, in 1944 and would be only about 92 or 93. Aren't any of them still alive?

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#15




I'm not sure an age of 122 is as mathematically improbable as suggested. As the linked article notes:
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That is, to test the plausibility of the two or threeyear gap between 119 and 122, we need to examine the conditional probability of somebody living to 122 given that they've already reached 119. 
#16




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If a person lives to age 110, then they are already an extreme outlier of human longevity and the extreme claims become even more extreme. I'm obviously not a statistician, but I would expect a distribution like #3 to #100 in that list. #1 and #2 seem like outliers. You see an expected distribution, more 110 year olds, fewer 111 year olds, even fewer 112 year olds, etc. down to the end at #3. It seems incredible that these top two should be such outliers and Calment's claim is a full three years older than the first outlier. Of course, I guess anything is possible, but is it likely given the known distribution? I thought the comparison of the ears and the chin was very compelling. 
#17




[Responding to Kimstu] I think the correct statistical test is not quite that, it's the probability of seeing a single 122yearold given the entire distribution of everyone else. But it's hard to imagine that any statistical test would be at all reliable, because you have to extrapolate the unknown extreme tail of the distribution.
Last edited by Riemann; 01022019 at 09:58 PM. 
#18




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In other words, the inference that there's something fishy if we're not seeing more 120yearolds than 122yearolds is not necessarily justified. To take another example, suppose somebody's randomly flipping a coin for a while and they, improbably, flip thirtyfive heads in a row, but there were no other runs where they flipped only thirty heads in a row. In terms of basic probability, a 30heads run is more likely than a 35heads run so we ought to see more of the former, right? Should we assume that the 35heads run therefore looks suspicious? Not really: it comes down to a question of sample size and the law of large numbers and so forth. You cannot take it for granted that a particular type of very improbable event will be better represented in your limited sample than any type of event that's even more improbable. Quote:
But this is not how statistics works. Any more than it's necessarily suspect to have a 35heads run in coin flipping when you haven't had any 30heads runs. Quote:
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Last edited by Kimstu; 01022019 at 11:18 PM. 
#19




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30: 28 31: 14 32: 6 33: 2 34: 0 35: 1 If we see: 30: 4 31: 1 32: 0 33: 0 34: 0 35: 1 then I think that the guy claiming 35 is lying. 


#20




This is disappointing. The last few years of Calment's life, the wife and I sent her a birthday card from Bangkok. We addressed them simply, "Jeanne Calment, World's Oldest Person, Arles, France." They were never returned, so they must have reached her.
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Everything happens for a reason. But sometimes the reason is you are stupid and make bad decisions. Last edited by Siam Sam; 01032019 at 12:47 AM. 
#21




Once upon a time, I heard that at age 100 you have a steady chance of about 10% per year of dying. That data was only up to 110, though, after which there may be other degeneration that can increase the death rate. I don't have a reference, but there should be more uptodate information anyway.

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#23




Some recent research indicates that after turning 105, your chance of dying each year doesn't increase. From then on, your chance of living one more year is 50%. Up to that point, your chance of dying in the next year is a little more each year. Your chance of dying in the next year is more when you're 100 than when you're 90, which is more than when you're 80, which is more than when you're 70, which is more than when you're 60, etc.:
https://www.washingtonpost.com/news/...=.512e32f0a9e3 https://www.theguardian.com/science/...ngevenlonger 
#24




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114: 56 (undercounted, since the list only includes the 100 oldest.) 115: 24 116: 10 117: 7 118: 0 119: 1 120: 0 121: 0 122: 1 What model do you think rules out the outliers while allows for almost equal numbers of 116 and 117 year olds? What if we group by quarter year instead: 114.25: 22 114.50: 24 114.75: 11 115.00: 8 115.25: 7 115.50: 7 115.75: 2 116.00: 4 116.25: 3 116.50: 0 116.75: 3 117.00: 2 117.25: 1 117.50: 3 117.75: 0 118.00: 0 118.25: 0 118.50: 0 and so on. What model do you think we should fit to this? Fact is we're dealing with hundreds of millions of people generally dying much earlier than their hundredandtens. These are all outliers, and even if you remove the two oldest the data is still far from smooth. I'm not a statistician either, but I would expect a couple of extremes in any model that accurately reflects the bulk of the 100 oldest people list. Last edited by naita; 01032019 at 10:27 AM. 


#25




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The biggest points are the nose, ear, and jawline. They don't match Jeanne, but are dead on for Yvonne. 
#26




I'm a little unclear on this.
If she is a fraud, when exactly did she take over her mother's life? What age was she and what year? Was it just something that started as a tax dodge and she never expected to live long enough for it to become a thing, and now she's trapped in the lie? How old is she really, if she's a fraud? 
#27




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But I wonder: It might sort of be like measuring the decay of a radioactive sample with two isotopes. You start off with the faster decaying isotope breaking down quickly and after most of it is gone you are left with the slower decaying isotope contributing most of the radiation. So the resulting curve has a steep drop and then a much slower drop. With people you have a few "slow decay" folks. Once most of the "fast decay" folks are gone the curve reflects their death rate. 
#28




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This research alleges that it was actually Jeanne who died and Yvonne assumed her mother's identity for tax purposes because the law at the time would have required a hefty inheritance tax to transfer her properties (and the family had first hand experience of this when a different family member died in 1931). They were on shaky financial grounds anyways as the family went bankrupt in 1937. There has been no formal counterargument by the Calment supporters, but from the snips and blurbs, the argument seems to be: How could a 36 year old pass for a 59 year old in a relatively tight knit community? Wouldn't the neighbors and all associates immediately figure it out? The rejoinder to that is that: 1) the family owned several properties throughout the country and became rather reclusive, and 2) several close friends and associates knew exactly what had happened and as it was in the middle of the Great Depression, they were all on board with the Calment's keeping what was theirs and screwing the government. 
#29




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The poor family who bought her apartment using a life estate would have legal grounds to sue but I doubt there's any money to be reclaimed. 


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#32




What did Yvonne (purportedly) die of? I'll admit that it seems surprising that the world's oldest person would have had a daughter who died at 36, if it was natural causes.

#33




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But even "all the coin flipping in the world" is nowhere near an infinite number of flips. You would have to have at least many, many billions of flips to be reasonably confident that the Law of Large Numbers would put the relative frequencies of the different lengths of headsruns close to their expected values. And there's no guarantee that "all the coin flipping in the world" amounts to many, many billions. So it would not surprise me in the least, statistically speaking, if somebody flipping a coin mere millions of times (which, by the way, would still require solid consecutive months of constant coinflipping) happened to come up with 4 runs of 30 heads, 1 run of 31, 1 run of 35, and no runs of 32, 33, or 34. As I tell my calculus students, "The basic problem with mathematical intuition is that there are too many numbers, and most of them are too big." It takes a lot of conscious scrutiny and checking to bring "what you would expect to see" in line with what we can mathematically demonstrate to be true. This objection is even more stringent when we're talking about the infinitesimally tiny sample size of known supercentenarians. We simply cannot extrapolate from theoretical expected values to any remotely reliable conclusions about a mere few dozen people. Another thing I tell my students is that besides the Law of Large Numbers there's also "the Lawlessness of Small Numbers": namely, small sample sizes cannot be trusted to agree with theoretically predicted results, because the noise of statistical fluctuations will drown out the signal of probabilistic outcomes. This fundamental mathematical fact about insufficient data doesn't change simply because insufficient data is all that's available. Statistics doesn't care that you really want to draw some mathematical inferences and have no way of getting enough additional data to make your inferences mathematically reliable. Too bad, pal: if your statistical reasoning about how this tiny set of outliers "ought" to behave is unreliable because the sample size is inadequate, then your attempted conclusions are invalid, and that's that. The same issue comes up a lot in other areas with a lot of empirical complications and limitations, such as studies trying to compare genetic vs. environmental influences on behavior, for example. When it's difficult or impossible to collect all the data you need for a scientifically reliable analysis, a lot of people try to argue that their analysis of the insufficient data should be considered reliable anyway, because it's the best we can do. Nope. Statistics doesn't work that way. 
#34




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Also, the daughter, Yvonne Calment Billiot, bore a son in 1926 who was raised by his grandmother Jeanne after Yvonne's death from pneumonia in 1934. It would be rather peculiar for the 36yearold mother of a sevenyearold son to successfully pass off her 59yearold mother's death as her own and assume the older woman's identity for the next 63 years, in a city where both women were well known. I'm not saying it couldn't happen, but I'd definitely want more concrete evidence in order to believe it. 


#35




Great posts, Kimstu.
To give a demonstration of the problems with trying to extrapolate from very small sample sizes, there's always Joe DiMaggio in baseball. He is best known for his 56game hitting streakthat is, he got at least one base hit in 56 consecutive games. The secondlongest hitting streak in well over 100 years of baseball belongs to Wee Wille Keeler of the old Baltimore Orioles, who hit safely in...45 straight games. Almost two weeks short of DiMaggio. There are about three dozen hitters with 3033game streaks, another dozen or so in the 3439 range, a half dozen in the 4045 range...and then DiMaggio, with a streak eleven games longer than anyone else, ever. But we're not going to conclude that the streak didn't happen, because of course it did. Was it unlikely? Sure. Was it very unlikely? That, too. Impossible? Nah. The "lawlessness of Small Numbers" [great phrase btwmay I steal it?] allows DiMaggio's streak to be real, and would also allow for a woman reaching 122 when no one else ever reached 120. [This is not to disagree with the idea that Calment was actually two peopleI don't have an informed opinion one way or the other, though I kinda like the ideajust to give an example of how outliers can happen in extremely extreme situations.] Last edited by Ulf the Unwashed; 01032019 at 05:41 PM. 
#36




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#37




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Another fun example: stolen base records, lifetime: 500s: 21 players 600s: 8 700s: 5 800s: 2 900s: 2 1000s: 0 1100s: 0 1200s: 0 1300s: 0 1400s: 1 Good ol' Rickey henderson! Last edited by Ulf the Unwashed; 01032019 at 09:36 PM. 
#38




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But is a baseball hitting streak a good comparison? That involves factors like skill, the strength of the hitter behind you (so you are not walked), running speed to beat infield ground balls, the quality of opposing pitching including the fact that DiMaggio would typically see the same pitcher for 3 to 5 atbats per game, but today's hitters see relievers, etc. But anyways, the idea of a mortality plateau is interesting. I guess the idea is that these people have a genetic immunity to things like heart disease, cancer, or diabetes: things which will likely get us in our 70s90s. But once it is shown that they are not susceptible to these things, they will not get them even at extreme ages. I wonder if anyone who has survived cancer or a heart attack, for examples, have ever lived to be even 100, let alone 110. 
#39




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But to address the similarities or differences, of course some hitters are more likely to get a 56game streak going. Yes, speed helps. yes, playing for an offensive powerhouse helps, because you get more plate appearances that way; yes, opposing pitching matters (DiMaggio didn't have to face the Yankee staff if nothing else); yes, not drawing many walks helps. Etc. Joey Gallo is never going to have a 20game hitting streak, let alone a 56game one. But the same can be said for longlived persons, as you actually note. It helps to live in a developed country, it helps to be born with good genes. It helps to eat well, I'm sure. It helps to not come down with cancer. Lots of factors which will make it extremely unlikely that some people will make it to 75, let alone 100, let alone 120, but which through luck (or "skill," if you want to consider "deciding not to jump out of airplanes" a skill) will make it possible for others to make it that far. Baseball isn;t a level playing field, but then again neither is mortality. 


#40




Outliers can be weird
I grabbed another statistic because it was there, from the realm of finance. I took IBM's daily percentage changes in their adjusted closing price. I also looked at daily percentage changes in the volume of traded IBM shares. UltraVires might reasonably question whether this is a good comparison. No: it's a terrible comparison, except for making my narrow point that outliers can be weird. Tack it on to the baseball example.
Sample size: 14,343 IBM closing prices daily percentage changes: median: 0 mean: .0003024 std dev: .015773 Largest 4 percentage changes: .1172 .1202 .129 .1316 That looks ok. But consider the smallest percentage changes: .2352 (10/19/1987) .1554 (10/18/2000) .1495 (10/21/1999) .1074 (12/15/1992) Those are all over the map. So outliers can be well behaved and they can be weird. (Though tacking on dates gives a hint of what the underlying process might be.) Let's look at percentage change in daily volume, something that most of us will have little intuition for, except that it will have high variance. median: .0132 mean: .0846 std dev: .5877 Largest percentage changes: 26 22.83 15 14.50 So we have a cluster, followed by 2 hops. Smallest percentage changes: .9630 (4/9/1962) .9363 (2/8/1962) .9309 (6/17/1991) .9248 (9/21/1983) We have one hop at the tail, which is actually more dramatic than it looks. It's a 27x drop vs a 16x drop. The dates mean little to me. 
#41




Some more statistical observations, looking at longevity data from the worlds oldest (dead) people.
I went and grabbed the list of verified oldest people from wikipedia and threw out all the ones who are still alive, leaving 92 humans who died after age 114 years, 93 days. When you look at the data by 'number of days lived since 114+93' (I would have made it a round 114, if I'd had the data...) it's messy. Even 92 data points is a moderately small set. You can call Calment an inexplicably far outlier, but you could also point to the area at around +250 days as being inexplicably low. Is there some weird factor suppressing deaths at age 114 and 10 months? It doesn't seem likely. It's just a random variation. Next, working on the model that after age X you have a constant whateverpercent chance of dying in each time period, I did three models to figure out what the mosty likely perday chance of survival was under three conditions: using all the data, removing just Jeanne, removing Jeanne and Sarah Knauss. The result was. All data: 99.802% per day Exclude Jeanne: 99.756% per day Exclude Jeanne and Sarah: 99.756% per day IOW if you make it to 114+93, on any given day your chance of making it to the next day is very close to 99.8%. Assuming Jeanne is an invalid data points makes a noticeable difference to the calculated value, but assuming Sarah is invalid makes nearly none. At this point, I'd say that the statistical argument for being suspicious of Sarah Knauss' age at death is basically DOA, but Jeanne needs a little more investigating. I did a plot of the number of people who have ever lived to an age of "n days after 114+93", plus the predicted values of how many people should have been alive, given the chances of death calculated above. The red line is using a chanceofdeathperday of 99.802%, the blue line is using 99.756%. The blue line certainly fits the data somewhat better. However, as you can see, BOTH lines fit the "Jeanne" data point reasonably well  given that we start with 92 people at age 114+93, both models predict that we're left with about half a person at day 2991 (Jeanne's death day). So this is consistent with Jeanne just being a notunreasonable outlier Furthermore, if we assume someone has already lived as long as Sarah Knauss, I calculate the chance of living another 1160 days (the difference between Sarah and Jeanne's age at death) to be .99756**1160 = 0.059 (5.9%). That's really not a particularly low chance, given that we measure thousands of different statistics about the world all the time. It certainly isn't statistically suspicious enough to base a conspiracy theory off.
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It is easier to fall than to climb ... letting go for the fall brings a wonderful feeling of ease and power  Katherine Kerr Daggerspell 
#42




As far as the photo evidence goes ... the article spends a lot of space on proving that bowtiehatgirl is Yvonne, not Jeanne. Yeah, okay, it's Yvonne, mislabelled as Jeanne (sometimes).
But I don't actually think hatgirl looks that much like the photos of old Jeanne. Yvonne has a snub nose  Jeanne has a pointy nose in her old photos, and old Jeanne also has a pointy nose. Her jaw's fuller, but that happens to everyone as they get older.
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It is easier to fall than to climb ... letting go for the fall brings a wonderful feeling of ease and power  Katherine Kerr Daggerspell 
#43




I don't buy it
Looking at all the threads posted here  thanks to the people who provided them, there is much that is fishy about Jeanne Calment's claim. Some of the claims are based on census data, which is notoriously unreliable. While there is proof of the both of both Jeanne and her daughter Yvonne, the evidence for the death of Yvonne at age 36 is very sketchy indeed. The photo evidence indicates that the older "Jeanne" is most likely Yvonne, and the fact the "Jeanne" was unusually fit for a centenarian is another issue.
Statistically, both Knauss and Calment are anomalies, outliers. If the oldest verified person is 117, why is there nobody who reached 118? 120? 121? There is always a cluster at the ends, when the record is broken it is only by a few weeks or days each time. It looks as if the French government knows that calment's claim is false but the whole thing has become a matter of national pride, and everything else flies out of the window. 
#44




Brayne Ded writes:
> . . . There is always a cluster at the ends . . . Well, no, there isn't. It isn't necessarily true that there will either be a few people a little beyond the end or that there won't be a few beyond the end. It's estimated that there are now about 20,000 people of age 105 or greater in the world. If it's really true that at 105 you're about 50% likely to die in each following year, then the chances that you will live to 117 is 2*(12), which is 1/4096. So about 5 of those 20,000 will live to 117, 2 or 3 will live to 118, and 1 will live to 119. Again, assuming that at 119, you have a 50% chance of living to 120, a 25% chance of living to 121, and a 12 1/2% chance of living to 122. If Calment had claimed to live to be 145, that would be very good evidence that she was lying. We would only expect 2*(26) people who live to 119 to live to 145. That means we think that the chance that a person now alive will live to 145 is less than 0.0000015%. That's a small enough probability that we would be justified in saying that it's too improbable. A chance of 12 1/2% is not small enough to say that that purely based on statistics that it's too unlikely. Note that this says nothing about any other evidence on whether Calment was lying. https://www.quora.com/Howmanypeopl...105yearsold 


#45




Is she that woman who claimed she only had one wrinkle and that was what she sat on?

#46




#47




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And then there is the question as to how reliable the documentary evidence is, if it is still available. And let us not forget the medical evidence; an examination of Calment's teeth would soon settle the issue. Also, an examination of Yvonne's grave, if it is indeed hers. Note that the burials of both Yvonne and Jeanne were done hastily, with few witnesses and no post mortem. It seems that there has been a cover up and the French government refuses to allow the case to examined. 
#48




dropzone's Law: As an online discussion of statistics grows longer, the probability that the discussion involves baseball approaches 1.

#49




Do you have any background in statistics, Brayne Ded? No, well, I have a master's degree in mathematics. Unless you tell me that you have a Ph.D. in statistics, I don't consider you more qualified than me to talk about this. There is nothing terribly surprising about a jump to 119 and 122 after several people at 117. Seven people made it to 117. On average a person who's 117 (or any age over 105) has a 50% chance of living one more year. Actually, there are slightly less people living to 118 or 119 or 120 on the list linked to below than one would expect at random, but, again, it's within a reasonable probability.
If you don't believe this, go to your nearest university and talk to someone in the mathematics department who specializes in probability. The university might have a separate department for statistics, so go there if there is one. Show them the table linked to below and ask them if it's that allfired surprising that there's one person living to 119 and one living to 122. See what they say. Again, I will not address any other part of the evidence about whether Jeanne Calment was lying. I am not an expert on that sort of evaluation of evidence, and I suspect that neither are you. I am a mathematician, and I have some qualifications to discuss the statistical evidence: https://en.wikipedia.org/wiki/Oldest_people 


#50




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If Brayne Ded has taken any college level course in probability, he would quickly encounter a number of counterintuitive results. This is one of them: while averages tend to be reasonable well behaved, outliers are typically not, since outliers are by definition small in number. A good way to get a sense of some of these apparent abnormalities is to play around with the random number generator in Excel. Use this function to obtain a random variable with a normal distribution (mean 0, standard deviation 1): PHP Code:
mean 0.046554367 st dev 0.960326581 The mean isn't exactly zero and the standard deviation isn't exactly 1, but they are close. Lowest 4 numbers: 2 clusters with 1 hop. 2.732902933 2.705766188 2.580533898 2.500981489 Largest 4 numbers: 4 hops. 3.308270247 3.132253566 2.838211351 2.628009157 Now don't get me wrong: the above isn't the proper statistical model by any means for longevity. It's simply designed to show that gaps between extreme values are by no means unusual. I could do a similar exercise with, say, 5 million observations in Stata and I would expect analogous results. But lots of people have Excel on their computer; for those who don't LibreOffice has a free spreadsheet program called Calc, which would also work. Or try locating any dataset with a sample above, say, 500. This is a pretty good thread actually. Ultravires made an entirely reasonable statistical observation: that's it was poorly ground is surprising, but not at all his fault. This isn't a statistical gimmick at work: it's a widely observed yet still surprising result. ETA: Rounding to some extent can also create these effects. Here are the 1st differences of above outliers: they aren't exactly evenly spaced, though they are a little better than the first eyeball of the data: Lowest numbers, 1st diffs: 0.03 0.13 0.08 Highest numbers, 1st diffs: 0.18 0.29 0.21 Note that this is a symmetric distribution, so in the perfect case the absolute value of those 1st differences would all be equal. They aren't close. 
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