Error (redirected from Experimental error)

error, in law: see appeal.

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error

In applied mathematics, the difference between a value and an estimate of that value. In statistics, a common example is the difference between the mean age of a given group of people (see mean, median, and mode) and that of a sample drawn from the group. In numerical analysis, an example of round-off error is the difference between the true value of pi and commonly substituted expressions like ²²⁄₇ and shorter versions like 3.14159. Truncation error results from using only the first few terms of an infinite series. Relative error is the ratio of the size of an error to the size of the quantity measured, and percentage error is relative error expressed as a percent.

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error [′er·ər]

(computer science)

An incorrect result arising from approximations used in numerical methods, rather than from a human mistake or computer malfunction.

(science and technology)

Any discrepancy between a computed, observed, or measured quantity and the true, specified, or theoretically correct value of that quantity.

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Error

Breeches Bible, the

the Geneva Bible, so dubbed because it stated that Adam and Eve made themselves breeches. [Br. Hist.: Brewer Dictionary, 101]

Cortez

alluded to in a poem by Keats, mistaken for Balboa, as discoverer of Pacific Ocean. [Br. Poetry: “On First Looking into Chapman’s Homer”]

Wicked Bible, the

misprinted a commandment as “Thou shalt commit adultery.” [Br. Hist.: Brewer Dictionary, 102]

seacoast of Bohemia

Shakespearean setting in a land with no seacoast. [Br. Drama: Shakespeare The Winter’s Tale, III,iii]

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1.		error - A discrepancy between a computed, observed, or measured value or condition and the true, specified, or theoretically correct value or condition.
2.	(programming)	error - A mental mistake made by a programmer that may result in a program fault.
3.		error - (verb) What a program does when it stops as result of a programming error.

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Error 

in automatic control systems, the difference between the set point and the actual value of the quantity being controlled in a control process. At any given moment, the error can be regarded as the sum of the static error—the error under steady-state conditions—and the dynamic error—the error in a transient response. In the statistical analysis of automatic control systems, the distinction between steady-state and transient errors loses its meaning, and the quality of performance of such a system is evaluated by criteria associated with the probability characteristics of the error. An example of such a criterion is the minimum mean-square error.

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Error 

When a number a is taken as the approximate value of a quantity whose exact value is x, the error of a is the difference x – a, which is also called the absolute error. The ratio of x – a to a is called the relative error. An error is usually characterized by indicating its maximum possible value. The maximum possible value of the absolute error is the number Δ (a) such that ǀx – aǀ ≤ Δ(a). The maximum possible value of the relative error is the number δ(a) such that

The maximum values of relative errors are often expressed as percentages. The numbers Δ(a) and δ(a) are taken as small as possible.

If a is the approximate value of x with a maximum absolute error of Δ(a), this fact can be written x = a ± Δ(a). The analogous expression for the relative error is x = a(1 ± δ(a)).

The maximum values of the absolute and relative errors indicate the maximum possible divergence between x and a. In addition to these values, an error is often characterized by the nature of its origin and by the frequency of occurrence of different values of x – a. The methods of probability theory are used in this approach to errors.

The error of the result in the numerical solution of a problem is caused by inaccuracies intrinsic to the formulation of the problem and to the means used to solve it. Errors stemming from the inaccuracy of a mathematical description of an actual process—for example, from an inaccurate statement of the original data—are said to be inherent errors. Errors of method arise because of the inaccuracy of the method used in solving the problem. Computational errors are the result of inaccuracies in computations.

When computations are performed, initial errors pass in succession from operation to operation, accumulating and giving rise to new errors. The appearance and propagation of errors in computational work are studied by numerical analysis.

REFERENCES

Berezin, I. S., and N. P. Zhidkov. Metody vychislenii, 3rd ed., vol. 1. Moscow, 1966.
Bakhvalov, N. S. Chislennye metody. Moscow, 1973.

G. D. KIM