Random in the context of Random number generation


Random in the context of Random number generation

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⭐ Core Definition: Random

In common usage, randomness is the apparent or actual lack of definite patterns or predictability in information. A random sequence of events, symbols or steps often has no order and does not follow an intelligible pattern or combination. Individual random events are, by definition, unpredictable, but if there is a known probability distribution, the frequency of different outcomes over repeated events (or "trials") is predictable. For example, when throwing two dice, the outcome of any particular roll is unpredictable, but a sum of 7 will tend to occur twice as often as 4. In this view, randomness is not haphazardness; it is a measure of uncertainty of an outcome. Randomness applies to concepts of chance, probability, and information entropy.

The fields of mathematics, probability, and statistics use formal definitions of randomness, typically assuming that there is some 'objective' probability distribution. In statistics, a random variable is an assignment of a numerical value to each possible outcome of an event space. This association facilitates the identification and the calculation of probabilities of the events. Random variables can appear in random sequences. A random process is a sequence of random variables whose outcomes do not follow a deterministic pattern, but follow an evolution described by probability distributions. These and other constructs are extremely useful in probability theory and the various applications of randomness.

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👉 Random in the context of Random number generation

Random number generation is a process by which, often by means of a random number generator (RNG), a sequence of numbers or symbols is generated that cannot be reasonably predicted better than by random chance. This means that the particular outcome sequence will contain some patterns detectable in hindsight but impossible to foresee. True random number generators can be hardware random-number generators (HRNGs), wherein each generation is a function of the current value of a physical environment's attribute that is constantly changing in a manner that is practically impossible to model. This would be in contrast to so-called random number generations done by pseudorandom number generators (PRNGs), which generate pseudorandom numbers that are in fact predetermined—these numbers can be reproduced simply by knowing the initial state of the PRNG and the method it uses to generate numbers. There is also a class of non-physical true random number generators (NPTRNG) that produce true random numbers without an access to a dedicated hardware source, by scavenging entropy that is present in the computer system. See the details in True vs. pseudo-random numbers.

Various applications of randomness have led to the development of different methods for generating random data. Some of these have existed since ancient times, including well-known examples like the rolling of dice, coin flipping, the shuffling of playing cards, the use of yarrow stalks (for divination) in the I Ching, as well as countless other techniques. Because of the mechanical nature of these techniques, generating large quantities of sufficiently random numbers (important in statistics) required much work and time. Thus, results would sometimes be collected and distributed as random number tables.

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Random in the context of Information

Information is an abstract concept that refers to something which has the power to inform. At the most fundamental level, it pertains to the interpretation (perhaps formally) of that which may be sensed, or their abstractions. Any natural process that is not completely random and any observable pattern in any medium can be said to convey some amount of information. Whereas digital signals and other data use discrete signs to convey information, other phenomena and artifacts such as analogue signals, poems, pictures, music or other sounds, and currents convey information in a more continuous form. Information is not knowledge itself, but the meaning that may be derived from a representation through interpretation.

The concept of information is relevant or connected to various concepts, including constraint, communication, control, data, form, education, knowledge, meaning, understanding, mental stimuli, pattern, perception, proposition, representation, and entropy.

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Random in the context of Noise (signal processing)

In signal processing, noise is a general term for unwanted (and, in general, unknown) modifications that a signal may suffer during capture, storage, transmission, processing, or conversion.

Sometimes the word is also used to mean signals that are random (unpredictable) and carry no useful information; even if they are not interfering with other signals or may have been introduced intentionally, as in comfort noise.

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Random in the context of Arbitrariness

Arbitrariness is the quality of being "determined by chance, whim, or impulse, and not by necessity, reason, or principle". It is also used to refer to a choice made without any specific criterion or restraint.

Arbitrary decisions are not necessarily the same as random decisions. For example, during the 1973 oil crisis, Americans were allowed to purchase gasoline only on odd-numbered days if their license plate was odd, and on even-numbered days if their license plate was even. The system was well-defined and not random in its restrictions; however, since license plate numbers are completely unrelated to a person's fitness to purchase gasoline, it was still an arbitrary division of people. Similarly, schoolchildren are often organized by their surname in alphabetical order, a non-random yet an arbitrary method—at least in cases where surnames are irrelevant.

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Random in the context of Pitting corrosion

Pitting corrosion, or pitting, is a form of extremely localized corrosion that leads to the random creation of small holes in metal. The driving power for pitting corrosion is the depassivation of a small area, which becomes anodic (oxidation reaction) while an unknown but potentially vast area becomes cathodic (reduction reaction), leading to very localized galvanic corrosion. The corrosion penetrates the mass of the metal, with a limited diffusion of ions.

Another term arises, pitting factor, which is defined as the ratio of the depth of the deepest pit (from localized corrosion) to the average penetration depth (mean thickness of the corrosion layer produced by the general uniform corrosion), which can be calculated based on the weight loss and corrosion products density.

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Random in the context of Cleromancy

Cleromancy is a form of sortition (casting of lots) in which an outcome is determined by means that normally would be considered random, such as the rolling of dice (astragalomancy), but that are sometimes believed to reveal the will of a deity.

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Random in the context of Stochastic

Stochastic (/stəˈkæstɪk/; from Ancient Greek στόχος (stókhos) 'aim, guess') is the property of being well-described by a random probability distribution. Stochasticity and randomness are technically distinct concepts: the former refers to a modeling approach, while the latter describes phenomena; in everyday conversation these terms are often used interchangeably. In probability theory, the formal concept of a stochastic process is also referred to as a random process.

Stochasticity is used in many different fields, including image processing, signal processing, computer science, information theory, telecommunications, chemistry, ecology, neuroscience, physics, and cryptography. It is also used in finance (e.g., stochastic oscillator), due to seemingly random changes in the different markets within the financial sector and in medicine, linguistics, music, media, colour theory, botany, manufacturing and geomorphology.

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Random in the context of Pseudorandom Number Generator

A pseudorandom number generator (PRNG), also known as a deterministic random bit generator (DRBG), is an algorithm for generating a sequence of numbers whose properties approximate the properties of sequences of random numbers. The PRNG-generated sequence is not truly random, because it is completely determined by an initial value, called the PRNG's seed (which may include truly random values). Although sequences that are closer to truly random can be generated using hardware random number generators, pseudorandom number generators are important in practice for their speed in number generation and their reproducibility.

PRNGs are central in applications such as simulations (e.g. for the Monte Carlo method), electronic games (e.g. for procedural generation), and cryptography. Cryptographic applications require the output not to be predictable from earlier outputs, and more elaborate algorithms, which do not inherit the linearity of simpler PRNGs, are needed.

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Random in the context of Spoon lure

In sport fishing, a spoon lure is a fishing lure usually made of lustrous metal and with an oblong, usually concave shape like the bowl of a spoon. The spoon lure is mainly used to attract predatory fish by specular reflection of light, as well as the turbulences it creates when moving in water.

The design of the spoon lure is simple: the oblong, concave blade shape of the spoon will cause it to wabble randomly when towed or sinking through water, creating sparkles of light reflection that resemble those of a swimming bait fish's scales when looking from afar. The spoon wabbling also stirs up turbulences that can entice the fish to stalk and strike it. Fish normally use their lateral line system to follow the vortices produced by fleeing prey, and the oscillating movements of the spoon lure can imitate these. Different color variations and materials can be added to the classic spoon lure may also help catch fish. Silver- or gold-plated or dyed finishes can give the lure a more vibrant or brilliant appearance. Most spoon lures have at least one hook at the end, which tethers the fish's mouth when the fish swallows the spoon.

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Random in the context of Ergodic theory

Ergodic theory is a branch of mathematics that studies statistical properties of deterministic dynamical systems; it is the study of ergodicity. In this context, "statistical properties" refers to properties which are expressed through the behavior of time averages of various functions along trajectories of dynamical systems. The notion of deterministic dynamical systems assumes that the equations determining the dynamics do not contain any random perturbations, noise, etc. Thus, the statistics with which we are concerned are properties of the dynamics.

Ergodic theory, like probability theory, is based on general notions of measure theory. Its initial development was motivated by problems of statistical physics.

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Random in the context of Airy wave theory

In fluid dynamics, Airy wave theory (often referred to as linear wave theory) gives a linearised description of the propagation of gravity waves on the surface of a homogeneous fluid layer. The theory assumes that the fluid layer has a uniform mean depth, and that the fluid flow is inviscid, incompressible and irrotational. This theory was first published, in correct form, by George Biddell Airy in the 19th century.

Airy wave theory is often applied in ocean engineering and coastal engineering for the modelling of random sea states – giving a description of the wave kinematics and dynamics of high-enough accuracy for many purposes. Further, several second-order nonlinear properties of surface gravity waves, and their propagation, can be estimated from its results. Airy wave theory is also a good approximation for tsunami waves in the ocean, before they steepen near the coast.

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Random in the context of Wave height

In fluid dynamics, the wave height of a surface wave is the difference between the elevations of a crest and a neighboring trough. Wave height is a term used by mariners, as well as in coastal, ocean and naval engineering.

At sea, the term significant wave height is used as a means to introduce a well-defined and standardized statistic to denote the characteristic height of the random waves in a sea state, including wind sea and swell. It is defined in such a way that it more or less corresponds to what a mariner observes when estimating visually the average wave height.

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Random in the context of Birthday problem

In probability theory, the birthday problem asks for the probability that, in a set of n randomly chosen people, at least two will share the same birthday. The birthday paradox is the counterintuitive fact that only 23 people are needed for that probability to exceed 50%.

The birthday paradox is a veridical paradox: it seems wrong at first glance but is, in fact, true. While it may seem surprising that only 23 individuals are required to reach a 50% probability of a shared birthday, this result is made more intuitive by considering that the birthday comparisons will be made between every possible pair of individuals. With 23 individuals, there are 23 × 22/2 = 253 pairs to consider.

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Random in the context of Injury prevention

Injury prevention is an effort to prevent or reduce the severity of bodily injuries caused by external mechanisms, such as accidents, before they occur. Injury prevention is a component of safety and public health, and its goal is to improve the health of the population by preventing injuries and hence improving quality of life. Among laypersons, the term "accidental injury" is often used. However, "accidental" implies the causes of injuries are random in nature. Researchers prefer the term "unintentional injury" to refer to injuries that are nonvolitional but often preventable. Data from the U.S. Centers for Disease Control show that unintentional injuries are a significant public health concern: they are by far the leading cause of death from ages 1 through 44. During these years, unintentional injuries account for more deaths than the next three leading causes of death combined. Unintentional injuries also account for the top ten sources of nonfatal emergency room visits for persons up to age 9 and nine of the top ten sources of nonfatal emergency room visits for persons over the age of 9.

Injury prevention strategies cover a variety of approaches, many of which are classified as falling under the "3 Es" of injury prevention: education, engineering modifications, and enforcement/enactment of policies. Some organizations and researchers have variously proposed the addition of equity, empowerment, emotion, empathy, evaluation, and economic incentives to this list.

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Random in the context of Random walk

In mathematics, a random walk, sometimes known as a drunkard's walk, is a stochastic process that describes a path that consists of a succession of random steps on some mathematical space.

An elementary example of a random walk is the random walk on the integer number line which starts at 0, and at each step moves +1 or −1 with equal probability. Other examples include the path traced by a molecule as it travels in a liquid or a gas (see Brownian motion), the search path of a foraging animal, or the price of a fluctuating stock and the financial status of a gambler. Random walks have applications to engineering and many scientific fields including ecology, psychology, computer science, physics, chemistry, biology, economics, and sociology. The term random walk was first introduced by Karl Pearson in 1905.

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Random in the context of Thrill killing

A thrill killing is premeditated or random murder that is motivated by the sheer excitement of the act. While there have been attempts to categorize multiple murders, such as identifying "thrill killing" as a type of "hedonistic mass killing", actual details of events frequently overlap category definitions making attempts at such distinctions problematic.

Those identified as thrill killers are typically young males, but other profile characteristics may vary, according to Jack Levin, director of the Brudnick Center on Conflict and Violence at Northeastern University. The major common denominator among those who commit thrill killings is that they usually feel inadequate and are driven by a need to feel powerful. "To a certain extent, [thrill killers] may make their victims suffer so that they can feel good," said Levin. "Sadism is fairly common in thrill killings. The killer might torture, degrade, or rape his or her victim before he or she takes his or her life." They frequently have an "ideal victim type" who has certain physical characteristics.

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