# Collins / Monroe – Carter / Withrow Match Prediction | 29-08-2019 11:00

The second sampling-scheme will include those lengthy periods of a game where a dismissed player is replaced, during which the current batsman is preparing to take the field and has no runs. If people sample based on time-of-day rather than running-score they will often find that a new batsman has a score of zero when the total score that day was low, but humans will rarely sample a zero if one batsman continued piling on runs all day long. Therefore, sampling a non-zero score would tell us something about the likely final score the current batsman will achieve.

It is not true that the chance is half, whatever the number of runs currently scored; batting records give an empirical correlation between reaching a given score (50 say) and reaching any other, higher score (say 100). On the average, the chance of doubling the current tally may be half, but the chance of reaching 100 having scored 50 is much lower than reaching ten from five.

The title "Doomsday Argument" is arguably a misnomer. Its popularity as a way of referring to this concept is perhaps based on the widespread belief that there are more people now alive than have ever lived, which would make the current generation of humans statistically likely to be the last one. That being the case, the argument actually implies it is unlikely that this is the last generation. According to the Population Reference Bureau, however, the number of biologically modern humans who have ever lived and died is closer to 107 billion,[6] which is considerably more than the 7 billion alive today. It is further worth noting that even if the argument is accepted at face value, it does not entail extinctionhumanity could conversely evolve into something distinctly enough different that people born after that point would no longer compose part of the same reference group. Instead, it paints a relatively optimistic[citation needed] portrait of how long humanity is likely to last, even given current population growth. For both these reasons, the invocation of "doomsday" is misleading.

## Rangliste

Leslie and has since been independently discovered by J. Richard Gott[2] and Holger Bech Nielsen.[3] Similar principles of eschatology were proposed earlier by Heinz von Foerster, among others. It was first proposed in an explicit way by the astrophysicist Brandon Carter in 1983,[1] from which it is sometimes called the Carter catastrophe; the argument was subsequently championed by the philosopher John A. A more general form was given earlier in the Lindy effect,[4] in which for certain phenomena the future life expectancy is proportional to (though not necessarily equal to) the current age, and is based on decreasing mortality rate over time: old things endure.

Depending on the projection of world population in the forthcoming centuries, estimates may vary, but the main point of the argument is that it is unlikely that more than 1.2 trillion humans will ever live on Earth. Assuming that the world population stabilizes at 10 billion and a life expectancy of 80 years, it can be estimated that the remaining 1140 billion humans will be born in 9120 years. This problem is similar to the famous German tank problem. If Leslie's figure[5] is used, then 60 billion humans have been born so far, so it can be estimated that there is a 95% chance that the total number of humans N will be less than 2060 billion=1.2 trillion.

If a member did pass such a comment, it would indicate that they understood the DA sufficiently well that in fact 2 people could be considered to understand it, and thus there would be a 5% chance that 40 or more people would actually be interested. Also, of course, ignoring something because you only expect a small number of people to be interested in it is extremely short sightedif this approach were to be taken, nothing new would ever be explored, if we assume no a priori knowledge of the nature of interest and attentional mechanisms.

If the 'reference class' is the set of humans to ever be born, this gives N < 20n with 95% confidence (the standard Doomsday argument). However, he has refined this idea to apply to observer-moments rather than just observers. Nick Bostrom, considering observation selection effects, has produced a Self-Sampling Assumption (SSA): "that you should think of yourself as if you were a random observer from a suitable reference class".

## Three Best Over/Under Point Total Predictions: Week 1, Thursday Games

Consider a hypothetical insurance company that tries to attract drivers with long accident-free histories not because they necessarily drive more safely than newly qualified drivers, but for statistical reasons: the hypothetical insurer estimates that each driver looks for insurance quotes every year, so that the time since the last accident is an evenly distributed random sample between accidents. The chance of being more than halfway through an evenly distributed random sample is one-half, and (ignoring old-age effects) if the driver is more than halfway between accidents then he is closer to his next accident than his previous one.

Western demographics are now fairly uniform across ages, so a random birthday (n) could be (very roughly) approximated by a U(0,M] draw where M is the maximum lifespan in the census. How accurate would this estimate turn out to be? Without knowing the ladys age, the DA reasoning produces a rule to convert the birthday (n) into a maximum lifespan with 50% confidence (N). Gott's Copernicus method rule is simply: Prob (N < 2n) = 50%. The other half of the time 2n underestimates M, and in this case (the one Caves highlights in his example) the subject will die before the 2n estimate is reached. In this 'flat demographics' model Gott's 50% confidence figure is proven right 50% of the time. In this 'flat' model, everyone shares the same lifespan so N = M. If n happens to be less than (M)/2 then Gott's 2n estimate of N will be under M, its true figure.

This corresponds to the idea that humanity's growth may be exponential in time with doomsday having a vague prior pdf in time. The best way to compare this with Gott's Bayesian argument is to flatten the distribution from the vague prior by having the probability fall off more slowly with N (than inverse proportionally).

Applying Gott's DA to these variable definitions gives a 50% chance of doomsday within 50 years. The scientists' warning can be reconciled with the DA, however.[citation needed] The Doomsday clock specifically estimates the proximity of atomic self-destructionwhich has only been possible for about seventy years.[11] If doomsday requires nuclear weaponry then the Doomsday Argument 'reference class' is people contemporaneous with nuclear weapons. In this model, the number of people living through, or born after Hiroshima is n, and the number of people who ever will is N.