Hidden Variables
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Hidden Variables
Hidden variables may refer to: * Confounding, in statistics, an extraneous variable in a statistical model that correlates (directly or inversely) with both the dependent variable and the independent variable * Hidden transformation, in computer science, a way to transform a generic constraint satisfaction problem into a binary one by introducing new hidden variables * Hidden-variable theories, in physics, the proposition that statistical models of physical systems (such as Quantum mechanics) are inherently incomplete, and that the apparent randomness of a system depends not on collapsing wave functions, but rather due to unseen or unmeasurable (and thus "hidden") variables ** Local hidden-variable theory, in quantum mechanics, a hidden-variable theory in which distant events are assumed to have no instantaneous (or at least faster-than-light) effect on local events * Latent variables, in statistics, variables that are inferred from other observed variables See also * Hidden dep ...
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Confounding
In statistics, a confounder (also confounding variable, confounding factor, extraneous determinant or lurking variable) is a variable that influences both the dependent variable and independent variable, causing a spurious association. Confounding is a causal concept, and as such, cannot be described in terms of correlations or associations.Pearl, J., (2009). Simpson's Paradox, Confounding, and Collapsibility In ''Causality: Models, Reasoning and Inference'' (2nd ed.). New York : Cambridge University Press. The existence of confounders is an important quantitative explanation why correlation does not imply causation. Confounds are threats to internal validity. Definition Confounding is defined in terms of the data generating model. Let ''X'' be some independent variable, and ''Y'' some dependent variable. To estimate the effect of ''X'' on ''Y'', the statistician must suppress the effects of extraneous variables that influence both ''X'' and ''Y''. We say that ''X'' ...
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Hidden Transformation
The hidden transformation reformulates a constraint satisfaction problem in such a way all constraints have at most two variables. The new problem is satisfiable if and only if the original problem was, and solutions can be converted easily from one problem to the other. There are a number of algorithms for constraint satisfaction that work only on constraints that have at most two variables. If a problem has constraints with a larger arity (number of variables), conversion into a problem made of binary constraints allows for execution of these solving algorithms. Constraints with one, two, or more variables are called unary, binary, or ''higher-order'' constraints. The number of variables in a constraint is called its ''arity''. The hidden transformation converts an arbitrary constraint satisfaction problem into a binary one. The transformation is similar to that generating the dual problem. The problem is added new variables, one for each constraint of the original problem. The d ...
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Hidden-variable Theory
In physics, hidden-variable theories are proposals to provide explanations of quantum mechanical phenomena through the introduction of (possibly unobservable) hypothetical entities. The existence of fundamental indeterminacy for some measurements is assumed as part of the mathematical formulation of quantum mechanics; moreover, bounds for indeterminacy can be expressed in a quantitative form by the Heisenberg uncertainty principle. Most hidden-variable theories are attempts to avoid quantum indeterminacy, but possibly at the expense of requiring the existence of nonlocal interactions. Albert Einstein objected to aspects of quantum mechanics, and famously declared "I am convinced God does not play dice". Einstein, Podolsky, and Rosen argued by assuming local causality that quantum mechanics is an incomplete description of reality. Bell's theorem and subsequent experiments would later show that local hidden variables (a way for finding a complete description of reality) of ...
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Local Hidden-variable Theory
In the interpretation of quantum mechanics, a local hidden-variable theory is a hidden-variable theory that satisfies the condition of being consistent with local realism. This includes all types of the theory that attempt to account for the probabilistic features of quantum mechanics by the mechanism of underlying inaccessible variables, with the additional requirement from local realism that distant events be independent, ruling out ''instantaneous'' (that is, faster-than-light) interactions between separate events. The mathematical implications of a local hidden-variable theory in regard to the phenomenon of quantum entanglement were explored by physicist John Stewart Bell, who in 1964 proved that broad classes of local hidden-variable theories cannot reproduce the correlations between measurement outcomes that quantum mechanics predicts. The most notable exception is superdeterminism. Superdeterministic hidden-variable theories can be local and yet be compatible with observati ...
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Latent Variable
In statistics, latent variables (from Latin: present participle of ''lateo'', “lie hidden”) are variables that can only be inferred indirectly through a mathematical model from other observable variables that can be directly observed or measured. Such ''latent variable models'' are used in many disciplines, including political science, demography, engineering, medicine, ecology, physics, machine learning/artificial intelligence, bioinformatics, chemometrics, natural language processing, management and the social sciences. Latent variables may correspond to aspects of physical reality. These could in principle be measured, but may not be for practical reasons. In this situation, the term ''hidden variables'' is commonly used (reflecting the fact that the variables are meaningful, but not observable). Other latent variables correspond to abstract concepts, like categories, behavioral or mental states, or data structures. The terms ''hypothetical variables'' or ''hypothetical ...
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Hidden Dependency
Cognitive dimensions or cognitive dimensions of notations are design principles for notations, user interfaces and programming languages, described by researcher Thomas R.G. Green and further researched with Marian Petre. The dimensions can be used to evaluate the usability of an existing ''information artifact'', or as heuristics to guide the design of a new one, and are useful in Human-Computer Interaction design. Cognitive dimensions are designed to provide a lightweight approach to analyse the quality of a design, rather than an in-depth, detailed description. They provide a common vocabulary for discussing many factors in notation, UI or programming language design. Also, cognitive dimensions help in exploring the space of possible designs through ''design maneuvers'', changes intended to improve the design along one dimension. List of the cognitive dimensions Thomas Green originally defined 14 cognitive dimensions: ; Abstraction gradient : What are the minimum and maxim ...
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Hidden Side Effect
In computer science, an operation, function or expression is said to have a side effect if it modifies some state variable value(s) outside its local environment, which is to say if it has any observable effect other than its primary effect of returning a value to the invoker of the operation. Example side effects include modifying a non-local variable, modifying a static local variable, modifying a mutable argument passed by reference, performing I/O or calling other functions with side-effects. In the presence of side effects, a program's behaviour may depend on history; that is, the order of evaluation matters. Understanding and debugging a function with side effects requires knowledge about the context and its possible histories. Side effects play an important role in the design and analysis of programming languages. The degree to which side effects are used depends on the programming paradigm. For example, imperative programming is commonly used to produce side effects, to ...
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Infrequent Variables
Logic optimization is a process of finding an equivalent representation of the specified logic circuit under one or more specified constraints. This process is a part of a logic synthesis applied in digital electronics and integrated circuit design. Generally, the circuit is constrained to a minimum chip area meeting a predefined response delay. The goal of logic optimization of a given circuit is to obtain the smallest logic circuit that evaluates to the same values as the original one. The smaller circuit with the same function is cheaper, takes less space, consumes less power, have shorter latency, and minimizes risks of unexpected cross-talk, hazard of delayed signal processing, and other issues present at the nano-scale level of metallic structures on an integrated circuit. In terms of Boolean algebra, the optimization of a complex boolean expression is a process of finding a simpler one, which would upon evaluation ultimately produce the same results as the original one ...
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