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Scientific literacy is important for understanding, applying, and integrating concepts from a range of domains such as mathematics, chemistry, engineering, and physics, all of which are integrated into explanation for the theory of biological evolution.
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We think the basic statements (e.g. the body has to overcome drag; to push itself in a new direction it has to exercise a force in the opposite direction) and the equation of drag with some other minor considerations are necessary and sufficient arguments for the explanation of the theory, but should it require a more detailed rationale we would be grateful for more specific instructions.
The interested reader is referred to, e.g., Groom and Bailey (1989), Groom and Bahr (1992), and Chave and Smith (1994) for a more detailed explanation of the theory of galvanic distortion.
For a detailed explanation of the theories underpinning the VET scoring algorithm, readers are referred to Bernstein et al. ([2010]).
This could be a good explanation for the strand-slippage theory with an assumption that there is no bias in the rate of mis-pairing in genomic regions during the replication process.
Part of the explanation for game theory's relatively late entry into the field lies in the problems with which economists had historically been concerned.
The stem cell theory offers an explanation for the exceptions that other theories cannot offer and demonstrates great potential as a theory describing the pathogenesis of endometriosis.
For a detailed explanation on the theory of EA, SVD and Mohr diagrams related to the telluric distortion matrix, the reader is referred to Lilley (1993, 2012, 2015).
A further argument commonly advanced in support of realism is that it provides the best, or the only credible, explanation for the success of scientific theories.
Others have construed robustness arguments more along the lines of Putnam's "no miracle" argument for scientific realism, according to which the assumption of the reality of some theoretical entities is the best explanation for the predictive success of theories or, in the case of robustness, for the agreement of experimental results (Weber 2005, Ch. 8; Stegenga 2009).
In 1983 Robert Laughlin, now at Stanford University, proposed an explanation for the FQH effect, and although the theory was widely accepted, it included a strange concept: fractional charges.
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