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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 ...
Frequency-dependent selection may explain the high degree of polymorphism in the MHC. [12] In behavioral ecology, negative frequency-dependent selection often maintains multiple behavioral strategies within a species. A classic example is the Hawk-Dove model of interactions among individuals in a population.
The independent variable is the time (Levels: Time 1, Time 2, Time 3, Time 4) that someone took the measure, and the dependent variable is the happiness measure score. Example participant happiness scores are provided for 3 participants for each time or level of the independent variable.
The same is true for intervening variables (a variable in between the supposed cause (X) and the effect (Y)), and anteceding variables (a variable prior to the supposed cause (X) that is the true cause). When a third variable is involved and has not been controlled for, the relation is said to be a zero order relationship. In most practical ...
The independent variable is manipulated by the experimenter, and the dependent variable is measured. The signifying characteristic of a true experiment is that it randomly allocates the subjects to neutralize experimenter bias , and ensures, over a large number of iterations of the experiment, that it controls for all confounding factors.
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 ...
In models of mutualisms, the terms "type I" and "type II" functional responses refer to the linear and saturating relationships, respectively, between the benefit provided to an individual of species 1 (dependent variable) and the density of species 2 (independent variable).
A variable in an experiment which is held constant in order to assess the relationship between multiple variables [a], is a control variable. [2] [3] A control variable is an element that is not changed throughout an experiment because its unchanging state allows better understanding of the relationship between the other variables being tested.