Coefficient of variation and consistency?

AI Thread Summary
The coefficient of variation indicates the consistency of data, with a lower value signifying higher consistency. Consistency refers to reduced diversity and describes the scatter or dispersion within a dataset. In physical sciences, low variability can suggest that measurement errors are random, implying that the measured quantity is stable. This understanding of consistency is crucial for interpreting data reliability. Overall, the coefficient of variation serves as a key metric for assessing data consistency and variability.
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The coefficient of variation tells us about the consistency in the data. I know that the lower the coefficient of variation is, the higher will be the consistency in the data. What I don't understand is what is being meant by 'consistency' here. Could someone please explain that?
 
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Consistency in data means less diversity. It describes the scatter or dispersion of a distribution.

In some applications in physical sciences, low but noticeable variability in data may confirm the presence of random measurement errors, in which case one may assume that the quantity being measured is in fact stable, and that the variation between measurements is only due to observational error.
 

Thread 'Deductive proof in logic formal systems'

I was reading documentation about the soundness and completeness of logic formal systems. Consider the following $$\vdash_S \phi$$ where ##S## is the proof-system making part the formal system and ##\phi## is a wff (well formed formula) of the formal language. Note the blank on left of the turnstile symbol ##\vdash_S##, as far as I can tell it actually represents the empty set. So what does it mean ? I guess it actually means ##\phi## is a theorem of the formal system, i.e. there is a...
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