83,106
edits
Signal-to-noise ratio: Difference between revisions
no edit summary
Amwelladmin (talk | contribs) No edit summary |
Amwelladmin (talk | contribs) No edit summary Tags: Mobile edit Mobile web edit |
||
| Line 50: | Line 50: | ||
[[Social science]]s don’t have that get-out-of-jail-free card: they address precisely that kind of supervening cause: behaviour that is, intrinsically, ''un''predictable. Psychology, sociology, anthropology, economics — these concern themselves with human agents, who ''are'' influenced by each other — which is why we don’t use physical science to predict their behaviour. Social sciences have to deal with the inherently complex, non-Gaussian interactions between human beings.<ref>physical sciences set up closed logical systems within which their rules will work, and often these systems are dramatically simplified as compared with anything you see in the real world: Newton, for example, assumes a frictionless, stationery, stable, neutral frame of reference: circumstances which, in any observed environment, do not and ''cannot'' not exist. {{author|Nancy Cartwright}} calls these structures “[[nomological machine]]s”. Because of this explicit caveat, we can put any variances between Newton’s prediction and the observed outcome down not to [[falsification]], but to the messy real world “contaminating” the idealised experimental conditions. Hence, the proverbial [[crisp packet blowing across St Mark’s Square]].</ref> | [[Social science]]s don’t have that get-out-of-jail-free card: they address precisely that kind of supervening cause: behaviour that is, intrinsically, ''un''predictable. Psychology, sociology, anthropology, economics — these concern themselves with human agents, who ''are'' influenced by each other — which is why we don’t use physical science to predict their behaviour. Social sciences have to deal with the inherently complex, non-Gaussian interactions between human beings.<ref>physical sciences set up closed logical systems within which their rules will work, and often these systems are dramatically simplified as compared with anything you see in the real world: Newton, for example, assumes a frictionless, stationery, stable, neutral frame of reference: circumstances which, in any observed environment, do not and ''cannot'' not exist. {{author|Nancy Cartwright}} calls these structures “[[nomological machine]]s”. Because of this explicit caveat, we can put any variances between Newton’s prediction and the observed outcome down not to [[falsification]], but to the messy real world “contaminating” the idealised experimental conditions. Hence, the proverbial [[crisp packet blowing across St Mark’s Square]].</ref> | ||
===You can’t prove things that haven't happened yet with data=== | |||
It is said that the NASA scientists who raised the fear that damage to the space shuttle Columbia on launch posed a risk of catastrophic loss the the spacecraft on re-entry were required to prove their hunch with data. | |||
Leaving aside the difficulty with collecting ''any'' data about a the exterior of a vehicle travelling thousands of miles per hour in orbital space above the earth's atmosphere, let alone analyzing and drawing conclusions from it and the short period of time before it was due to come back to earth, note the profound logical fallacy with this request. At the point it was made, ''no'' shuttles had disintegrated on re-entry, notwithstanding that several head sustained minor damage on launch. There was, therefore, ''no'' data supported the scientists’ fear. | |||
''This did not mean the scientists were wrong'', as the world observed to its horror on 1 February 2003. | |||
===Behaviourism and ''The Ghost in the Machine''=== | ===Behaviourism and ''The Ghost in the Machine''=== | ||