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Different concepts of errors (construct validity, external validity, internal validity, bias, random error, type S and M errors, confounding, batch effects, regression to the mean) and corresponding controls are explained in the context of experimental design.
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This review introduces the fundamental concepts of error analysis as they apply to a wide range of metabolomics experimental designs and it discusses current methodologies for determining the propagation of uncertainty in appropriate metabolomics data analysis.
For this purpose, the concept of error expectation is introduced.
One such difficulty becomes apparent if we asked what actual work the concept of error probability does.
Furthermore, the concept of "error" is not explained well in the study.
The study discusses the concept of error estimation in linear elastodynamics.
"Fallibilism, correctly understood, implies the possibility, not the impossibility, of knowledge, because the very concept of error, if taken seriously, implies that truth exists and can be found".
We describe a microarray design based on the concept of error-correcting codes from digital communication theory.
A largely used concept of error control in such multiple testing is the expected proportion of falsely rejected hypotheses, or False Discovery Rate (FDR).
The concept of error-cancelling balanced reactions is used to calculate a distribution of possible values for the standard enthalpy of formation of each species.
Additionally, the concept of error handling is shown as a way to handle unexpected behavior inside the code, and to correct errors when possible.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com