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In fact, many philosophers and scientists accept the fallibility of statistics, and find it more important that statistical methods are understood and applied correctly.
The author captures this development and explains it in the context of the zeitgeist of modern physics: What revolutionary ideas did Feynman have, what contribution did he make to the development of quantum mechanics and quantum field theory, how can Feynman's methods be understood?
Everything that is said below about "method" must be understood in the light of this general proviso.
The behavior of a method can be understood simply as a relationship between its parameters and its return value, with no side effects on any other part of the program.
Thus, the systematic bias for each method should be understood and considered during data integration.
The method can be understood easily and used conveniently by non-statisticians.
Consequently, the limitations of this method must be understood and taken into consideration when examining the final gene rankings.
First, our method can be understood more easily and used with greater convenience by non-statisticians because the procedure of constructing the model fully agrees with the practical screening procedure.
Supertree methods can be understood as generalizations of consensus methods, that is, when applying a supertree algorithm in the consensus setting, the result should then be equivalent to the consensus.
Using investigated methods it was understood that strong correlation between porosity and permeability was only found in flow units defined based on FZI method.
In this work, we show that such regularization methods may be understood in a Bayesian context.
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