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Doomsday Argument
The doomsday argument (DA), or Carter catastrophe, is a probabilistic argument that claims to predict the future population of the human species based on an estimation of the number of humans born to date. The doomsday argument was originally proposed by the astrophysicist Brandon Carter in 1983, leading to the initial name of the Carter catastrophe. The argument was subsequently championed by the philosopher John A. Leslie and has since been independently conceived by J. Richard Gott and Holger Bech Nielsen. Similar principles of eschatology were proposed earlier by Heinz von Foerster, among others. A more general form was given earlier in the Lindy effect, which proposes that for certain phenomena, the future life expectancy is proportional to (though not necessarily equal to) the current age and is based on a decreasing mortality rate over time. Summary The premise of the argument is as follows: suppose that the total number of human beings who will ever exist is fixed. ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Heinz Von Foerster
Heinz von Foerster (; November 13, 1911 – October 2, 2002) was an Austrian-American scientist combining physics and philosophy, and widely attributed as the originator of second-order cybernetics. He was twice a Guggenheim fellow (1956–57 and 1963–64) and also was a fellow of the American Association for the Advancement of Science, 1980. He is well known for his doomsday equation, published in a 1960 issue of ''Science'', predicting that the hyperbolic growth of the Earth's population will result in the instantaneous disappearance of all humans on Friday, 13 November, A.D. 2026. As a polymath, he wrote nearly two hundred professional papers, gaining renown in fields ranging from computer science and artificial intelligence to epistemology, and researched high-speed electronics and electro-optics switching devices as a physicist, and in biophysics, the study of memory and knowledge. He worked on cognition based on neurophysiology, mathematics, and philosophy and was called ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Longevity
Longevity may refer to especially long-lived members of a population, whereas ''life expectancy'' is defined Statistics, statistically as the average number of years remaining at a given age. For example, a population's life expectancy at birth is the same as the average age at death for all people born in the same year (in the case of Cohort (statistics), cohorts). Longevity studies may involve putative methods to extend life. Longevity has been a topic not only for the scientific community but also for writers of Hyperborei, travel, science fiction, and utopian novels. The legendary fountain of youth appeared in the work of the Ancient Greek historian Herodotus. There are difficulties in authenticating the longest human maximum life span, life span, owing to inaccurate or incomplete birth statistics. Fiction, legend, and folklore have proposed or claimed life spans in the past or future vastly longer than those verified by modern standards, and longevity narratives and unverif ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Bayes's Theorem
Bayes' theorem (alternatively Bayes' law or Bayes' rule, after Thomas Bayes) gives a mathematical rule for inverting conditional probabilities, allowing one to find the probability of a cause given its effect. For example, if the risk of developing health problems is known to increase with age, Bayes' theorem allows the risk to someone of a known age to be assessed more accurately by conditioning it relative to their age, rather than assuming that the person is typical of the population as a whole. Based on Bayes' law, both the prevalence of a disease in a given population and the error rate of an infectious disease test must be taken into account to evaluate the meaning of a positive test result and avoid the '' base-rate fallacy''. One of Bayes' theorem's many applications is Bayesian inference, an approach to statistical inference, where it is used to invert the probability of observations given a model configuration (i.e., the likelihood function) to obtain the probability o ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Bayesian Inference
Bayesian inference ( or ) is a method of statistical inference in which Bayes' theorem is used to calculate a probability of a hypothesis, given prior evidence, and update it as more information becomes available. Fundamentally, Bayesian inference uses a prior distribution to estimate posterior probabilities. Bayesian inference is an important technique in statistics, and especially in mathematical statistics. Bayesian updating is particularly important in the dynamic analysis of a sequence of data. Bayesian inference has found application in a wide range of activities, including science, engineering, philosophy, medicine, sport, and law. In the philosophy of decision theory, Bayesian inference is closely related to subjective probability, often called "Bayesian probability". Introduction to Bayes' rule Formal explanation Bayesian inference derives the posterior probability as a consequence of two antecedents: a prior probability and a "likelihood function" derive ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Improper Prior
A prior probability distribution of an uncertain quantity, simply called the prior, is its assumed probability distribution before some evidence is taken into account. For example, the prior could be the probability distribution representing the relative proportions of voters who will vote for a particular politician in a future election. The unknown quantity may be a parameter of the model or a latent variable rather than an observable variable. In Bayesian statistics, Bayes' rule prescribes how to update the prior with new information to obtain the posterior probability distribution, which is the conditional distribution of the uncertain quantity given new data. Historically, the choice of priors was often constrained to a conjugate family of a given likelihood function, so that it would result in a tractable posterior of the same family. The widespread availability of Markov chain Monte Carlo methods, however, has made this less of a concern. There are many ways to construct ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Normalizing Constant
In probability theory, a normalizing constant or normalizing factor is used to reduce any probability function to a probability density function with total probability of one. For example, a Gaussian function can be normalized into a probability density function, which gives the standard normal distribution. In Bayes' theorem, a normalizing constant is used to ensure that the sum of all possible hypotheses equals 1. Other uses of normalizing constants include making the value of a Legendre polynomial at 1 and in the orthogonality of orthonormal functions. A similar concept has been used in areas other than probability, such as for polynomials. Definition In probability theory, a normalizing constant is a constant by which an everywhere non-negative function must be multiplied so the area under its graph is 1, e.g., to make it a probability density function or a probability mass function. Examples If we start from the simple Gaussian function p(x) = e^, \quad x\in(-\infty,\ ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Prior Probability
A prior probability distribution of an uncertain quantity, simply called the prior, is its assumed probability distribution before some evidence is taken into account. For example, the prior could be the probability distribution representing the relative proportions of voters who will vote for a particular politician in a future election. The unknown quantity may be a parameter of the model or a latent variable rather than an observable variable. In Bayesian statistics, Bayes' rule prescribes how to update the prior with new information to obtain the posterior probability distribution, which is the conditional distribution of the uncertain quantity given new data. Historically, the choice of priors was often constrained to a conjugate family of a given likelihood function, so that it would result in a tractable posterior of the same family. The widespread availability of Markov chain Monte Carlo methods, however, has made this less of a concern. There are many ways to const ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Gregorian Calendar
The Gregorian calendar is the calendar used in most parts of the world. It went into effect in October 1582 following the papal bull issued by Pope Gregory XIII, which introduced it as a modification of, and replacement for, the Julian calendar. The principal change was to space leap years slightly differently to make the average calendar year 365.2425 days long rather than the Julian calendar's 365.25 days, thus more closely approximating the 365.2422-day tropical year, "tropical" or "solar" year that is determined by the Earth's revolution around the Sun. The rule for leap years is that every year divisible by four is a leap year, except for years that are divisible by 100, except in turn for years also divisible by 400. For example 1800 and 1900 were not leap years, but 2000 was. There were two reasons to establish the Gregorian calendar. First, the Julian calendar was based on the estimate that the average solar year is exactly 365.25 days long, an overestimate of a li ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Hyperbolic Growth
When a quantity grows towards a singularity under a finite variation (a " finite-time singularity") it is said to undergo hyperbolic growth. More precisely, the reciprocal function 1/x has a hyperbola as a graph, and has a singularity at 0, meaning that the limit as x \to 0 is infinite: any similar graph is said to exhibit hyperbolic growth. Description If the output of a function is inversely proportional to its input, or inversely proportional to the difference from a given value x_0, the function will exhibit hyperbolic growth, with a singularity at x_0. In the real world hyperbolic growth is created by certain non-linear positive feedback mechanisms. Comparisons with other growth functions Like exponential growth and logistic growth, hyperbolic growth is highly nonlinear, but differs in important respects. These functions can be confused, as exponential growth, hyperbolic growth, and the first half of logistic growth are convex functions; however their asymptotic behav ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Sebastian Von Hoerner
Sebastian Rudolf Karl von Hoerner (15 April 1919 – 7 January 2003) was a German astrophysicist and radio astronomer. He was born in Görlitz, Lower Silesia. During WW II, Von Hoerner served in the German Army on the Eastern Front. A bullet struck a pair of binoculars he was wearing on a strap around his neck, ricocheted up and blinded him in one eye. He was sent to Germany to recover and was there when the Front collapsed. After the end of World War II he studied physics at University of Göttingen. He obtained his doctorate at the same university in 1951 as Carl Friedrich von Weizsäcker. Together they conducted simulations that studied the formation of stars and globular clusters. He continued this work at Astronomical Calculation Institute (University of Heidelberg) with Walter Fricke. He obtained his habilitation in 1959 at the University of Heidelberg. In 1962 he moved to National Radio Astronomy Observatory ( Green Bank, West Virginia), where he collaborated, inter al ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
World Population Since 10,000 BCE (OurWorldInData Series), OWID
The world is the totality of entities, the whole of reality, or everything that exists. The nature of the world has been conceptualized differently in different fields. Some conceptions see the world as unique, while others talk of a "plurality of worlds". Some treat the world as one simple object, while others analyze the world as a complex made up of parts. In scientific cosmology, the world or universe is commonly defined as "the totality of all space and time; all that is, has been, and will be". Theories of modality talk of possible worlds as complete and consistent ways how things could have been. Phenomenology, starting from the horizon of co-given objects present in the periphery of every experience, defines the world as the biggest horizon, or the "horizon of all horizons". In philosophy of mind, the world is contrasted with the mind as that which is represented by the mind. Theology conceptualizes the world in relation to God, for example, as God's creation, ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Science (magazine)
''Science'' is the peer-reviewed academic journal of the American Association for the Advancement of Science (AAAS) and one of the world's top academic journals. It was first published in 1880, is currently circulated weekly and has a subscriber base of around 130,000. Because institutional subscriptions and online access serve a larger audience, its estimated readership is over 400,000 people. ''Science'' is based in Washington, D.C., United States, with a second office in Cambridge, UK. Contents The major focus of the journal is publishing important original scientific research and research reviews, but ''Science'' also publishes science-related news, opinions on science policy and other matters of interest to scientists and others who are concerned with the wide implications of science and technology. Unlike most scientific journals, which focus on a specific field, ''Science'' and its rival ''Nature'' cover the full range of scientific disciplines. According to the '' ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
