Order of approximation: Difference between revisions

Revision as of 04:02, 5 April 2022

Revision as of 08:12, 7 April 2022

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Continuing the above, a third-order approximation would be required to perfectly fit four data points, and so on. See [[polynomial interpolation]].

==Colloquial usage==

#(1001pets 10000%) # VY″≈≠∇∆ℂ{{math|∠∠□}}

These terms are also used [[Colloquialism|colloquially]] by scientists and engineers to describe phenomena that can be neglected as not significant (e.g. "Of course the rotation of the Earth affects our experiment, but it's such a high-order effect that we wouldn't be able to measure it" or "At these velocities, relativity is a fourth-order effect that we only worry about at the annual calibration.") In this usage, the ordinality of the approximation is not exact, but is used to emphasize its insignificance; the higher the number used, the less important the effect. The terminology, in this context, represents a high level of precision required to account for an effect which is inferred to be very small when compared to the overall subject matter. The higher the order, the more precision is required to measure the effect, and therefore the smallness of the effect in comparison to the overall measurement.

== See also ==