Talk:Fudge factor

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refers to the margin for additional time, cost, or error that is added to a planned assignment or project because of the uncertainty in planning and estimating requirements. During the course of CI projects, the direction, questions, and/or objectives may change, hence creating unforeseen additional requirements for fact-finding. This extra margin - also known as the fudge or error factor - usually adds another 10 to 15 percent to the overall estimation. [1]

Einstein's fudge factor

Perhaps mention Einstein's fudge factor and how he believed it to be the single greatest blunder of his scientific career? 24.222.121.193 02:27, 1 August 2006 (UTC)[reply]

As Einstein first introduced the cosmological constant (1917), it was a fudge to his 1916 theory (and his stated aesthetics) because he didn't like that his theory predicted non-static cosmologies. ^[1] However, as a simple free parameter unbounded by the math that makes General Relativity work, General Relativity with a cosmological constant is a 2-parameter model of gravity, not a privileged parameter proportional to Newton's constant and a less privileged "fudge factor." 24.6.25.154 (talk) 11:06, 23 March 2017 (UTC)[reply]

^ http://scienceblogs.com/startswithabang/2013/05/17/einsteins-greatest-blunder-was-really-a-blunder/

Dark Matter and Dark Energy are parameters of ΛCDM cosmologies, not fudge factors

The evidence for the existence of a clumpy invisible something that makes galaxies, clusters of galaxies and the universe as a whole more massive than just the baryonic matter found by auditing stars and gas clouds is quite robust. The evidence that the universe is far flatter than 1-parameter General Relativity allows in the face of just baryonic matter and the cold dark matter supports both "dark energy" or 2-parameter General Relativity about equally well so the terms are effectively synonymous given our limited ability to test them. Multiple lines of evidence converge on supporting a narrow range of Cold Dark Matter and Dark Energy densities, and those lines of evidence are documented on the linked pages, so there is no need to label these model parameters as they are used today with the label "fudge factor" which is pejorative in math and physics. The single 20-year-old pop cosmology book used as a reference^[1] is thin evidence to indict modern cosmological models. 24.6.25.154 (talk) 11:06, 23 March 2017 (UTC)[reply]

^ Donald Goldsmith (1997), Einstein's Greatest Blunder?: The Cosmological Constant and Other Fudge Factors in the Physics of the Universe, Harvard University Press, ISBN 9780674242425

Going Rate?

How about some reference to the observed innacuracy of a time piece (i.e. the going rate). Important in, for example, sea faring and exploration when accurate assessments of local time and absolute time (e.g. at the greenwich meridian) are needed to effectively calculate longitude?

Any timepiece would have a tendency to be slightly fast or slightly slow depending on how it was manufactured. This error would be present at a constant rate (ie the going rate). Knowing it (by calibrating the timepiece to absolute time at the point of manufacture) one could then factor this in to calculations of longitude made with that timepiece.

At least, I believe that is the origin of the phrase, and I don't have access to the web as a whole to check! Sorry... 82.211.95.178 16:11, 1 August 2007 (UTC)[reply]

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Ryan Wolfurt

What exactly makes the case of Ryan Wolfurt so outstanding to serve as an example to be mentioned on wikipedia? Also the caption and segmentation make no sense for me. --85.158.137.196 (talk) 14:59, 19 July 2010 (UTC)[reply]

Mugglefuggled

Error estimation is not fudging. It's actually the opposite of that, the entire § should be removed. 98.4.124.117 (talk) 20:22, 8 February 2017 (UTC)[reply]

[1] ttp://scienceblogs.com/startswithabang/2013/05/17/einsteins-greatest-blunder-was-really-a-blunder/

[2] Donald Goldsmith (1997), Einstein's Greatest Blunder?: The Cosmological Constant and Other Fudge Factors in the Physics of the Universe, Harvard University Press, ISBN 9780674242425

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