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A variable is considered dependent if it depends on an independent variable. Dependent variables are studied under the supposition or demand that they depend, by some law or rule (e.g., by a mathematical function), on the values of other variables. Independent variables, in turn, are not seen as depending on any other variable in the scope of ...
In computer science and logic, a dependent type is a type whose definition depends on a value. It is an overlapping feature of type theory and type systems.In intuitionistic type theory, dependent types are used to encode logic's quantifiers like "for all" and "there exists".
In the theory of electrical networks, a dependent source is a voltage source or a current source whose value depends on a voltage or current elsewhere in the network. [ 1 ] Dependent sources are useful, for example, in modeling the behavior of amplifiers.
If the dependent variable is continuous—either interval level or ratio level, such as a temperature scale or an income scale—then simple regression can be used. If both variables are time series , a particular type of causality known as Granger causality can be tested for, and vector autoregression can be performed to examine the ...
Standardization of the coefficient is usually done to answer the question of which of the independent variables have a greater effect on the dependent variable in a multiple regression analysis where the variables are measured in different units of measurement (for example, income measured in dollars and family size measured in number of individuals).
An anti-dependency occurs when an instruction requires a value that is later updated. A violation of an anti-dependency leads to a write-after-read (WAR) hazard.. In the following example, instruction 2 anti-depends on instruction 3 — the ordering of these instructions cannot be changed, nor can they be executed in parallel (possibly changing the instruction ordering), as this would affect ...
Using productivity weighted labor force dependency ratio (PWLFDR) suggests that even an aging or decreasing population can maintain a stable support for the dependent (primarily ageing) population by increasing its productivity. A consequence from PWLFDR assessments is the recommendation to invest in education and life-long learning, child ...
Logistic regression is used in various fields, including machine learning, most medical fields, and social sciences. For example, the Trauma and Injury Severity Score (), which is widely used to predict mortality in injured patients, was originally developed by Boyd et al. using logistic regression. [6]