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Non-standard errors
(2021)
In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in sample estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: non-standard errors. To study them, we let 164 teams test six hypotheses on the same sample. We find that non-standard errors are sizeable, on par with standard errors. Their size (i) co-varies only weakly with team merits, reproducibility, or peer rating, (ii) declines significantly after peer-feedback, and (iii) is underestimated by participants.
It is shown that in the case of metals connected by a first order conductor the decomposition of formic acid is less at the element of lower work function while it is more at the element of higher work function. The metals used were Ni, Cd, Zn. The results correspond to the investigations of other authors 1 who showed that the activation energy on alloys depends on how far the concentration of electrons is from full saturation of the lattice type. This effect is explicable in terms of the development of a contact potential, the conditions in the case of metals being similar to those in the case of alloys