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The theory of biases in the introduction process as a cause of orientation or direction in evolution has been explained as the convergence of two threads. [15] The first, from theoretical population genetics, is the explicit recognition by theoreticians (toward the end of the 20th century) that a correct treatment of evolutionary dynamics requires a rate-dependent process of introduction ...
Selection bias refers to the problem that, at pre-test, differences between groups exist that may interact with the independent variable and thus be 'responsible' for the observed outcome. Researchers and participants bring to the experiment a myriad of characteristics, some learned and others inherent.
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.
There are multiple formal definitions of "inherent bias" which depend on the particular field of study. In statistics , the phrase is used in relation to an inability to measure accurately and directly what one would wish to measure, meaning that indirect measurements are used which might be subject to unknown distortions.
Developmental drive is the inherent natural tendency of organisms and their ontogenetic trajectories to change in a particular direction (i.e. a bias towards a certain ontogenetic trajectory). [14] [5] [6] This type of bias is thought to facilitate adaptive evolution by aligning phenotypic variability with the direction of selection. [15] [12]
In psychology and cognitive science, a memory bias is a cognitive bias that either enhances or impairs the recall of a memory (either the chances that the memory will be recalled at all, or the amount of time it takes for it to be recalled, or both), or that alters the content of a reported memory. There are many types of memory bias, including:
In particular, bias (the expected value of the difference of an estimated parameter and the true underlying value) occurs if an independent variable is correlated with the errors inherent in the underlying process. There are several different possible causes of specification error; some are listed below.
The bias results in the model attributing the effect of the missing variables to those that were included. More specifically, OVB is the bias that appears in the estimates of parameters in a regression analysis , when the assumed specification is incorrect in that it omits an independent variable that is a determinant of the dependent variable ...