About Equal Sign

An approximation is anything that is intentionally similar but not exactly equal to something else.

Etymology and usage

The word ''approximation'' is derived from Latin ''approximatus'', from ''proximus'' meaning ''very near'' and the prefix ''ad-'' (''ad-'' before ''p'' becomes ap- by assimilation) meaning ''to''. Words like ''approximate'', ''approximately'' and ''approximation'' are used especially in technical or scientific contexts. In everyday English, words such as ''roughly'' or ''around'' are used with a similar meaning. It is often found abbreviated as ''approx.''

The term can be applied to various properties (e.g., value, quantity, image, description) that are nearly, but not exactly correct; similar, but not exactly the same (e.g., the approximate time was 10 o'clock).

Although approximation is most often applied to numbers, it is also frequently applied to such things as mathematical functions, shapes, and physical laws.

In science, approximation can refer to using a simpler process or model when the correct model is difficult to use. An approximate model is used to make calculations easier. Approximations might also be used if incomplete information prevents use of exact representations.

The type of approximation used depends on the available information, the degree of accuracy required, the sensitivity of the problem to this data, and the savings (usually in time and effort) that can be achieved by approximation.

Mathematics

Approximation theory is a branch of mathematics, a quantitative part of functional analysis. Diophantine approximation deals with approximations of real numbers by rational numbers.

Approximation usually occurs when an exact form or an exact numerical number is unknown or difficult to obtain. However some known form may exist and may be able to represent the real form so that no significant deviation can be found. For example, 1.5 × 10⁶ means that the approximation 1,500,000 has been measured to the nearest hundred thousand (the actual value is somewhere between 1,450,000 and 1,550,000), this is in contrast to the notation 1.500 × 10⁶ which measures 1,500,000 to the nearest thousand (therefore giving a true value somewhere between 1,499,500 and 1,500,500).

It also is used when a number is not rational, such as the number π, which often is shortened to 3.14159, or 1.414 as the shortened form of .

Numerical approximations sometimes result from using a small number of significant digits. Calculations are likely to involve rounding errors and other approximation errors. Log tables, slide rules and calculators produce approximate answers to all but the simplest calculations. The results of computer calculations are normally an approximation expressed in a limited number of significant digits, although they can be programmed to produce more precise results. Approximation can occur when a decimal number cannot be expressed in a finite number of binary digits.

Related to approximation of functions is the asymptotic value of a function, i.e. the value as one or more of a function's parameters becomes arbitrarily large. For example, the sum (''k''/2)+(''k''/4)+(''k''/8)+...(''k''/2^''n'') is asymptotically equal to ''k''. No consistent notation is used throughout mathematics and some texts use ≈ to mean approximately equal and ~ to mean asymptotically equal whereas other texts use the symbols the other way around.

Typography

The approximately equals sign, ≈, was introduced by British mathematician Alfred Greenhill.

LaTeX symbols

Symbols used in LaTeX markup.
* $\approx$ (\approx), usually to indicate approximation between numbers, like $\pi \approx 3.14$.
* $\not\approx$ (\not\approx), usually to indicate that numbers are not approximately equal (1 $\not\approx$ 2).
* $\simeq$ (\simeq), usually to indicate asymptotic equivalence between functions, like $f(n) \simeq 3n^2$. So writing $\pi \simeq 3.14$ would be wrong under this definition, despite wide use.
* $\sim$ (\sim), usually to indicate proportionality between functions, the same $f(n)$ of the line above will be $f(n) \sim n^2$.
* $\cong$ (\cong), usually to indicate congruence between figures, like $\Delta ABC \cong \Delta A'B'C'$.
* $\eqsim$ (\eqsim), usually to indicate that two quantities are equal up to constants.
* $\lessapprox$ (\lessapprox) and $\gtrapprox$ (\gtrapprox), usually to indicate that either the inequality holds or the two values are approximately equal.

Unicode

Symbols used to denote items that are approximately equal are wavy or dotted equals signs.
* : which is also sometimes used to indicate proportionality
* : which is also sometimes used to indicate proportionality
* : another combination of "≈" and "=", which is used to indicate isomorphism or congruence
*
*
*
*
* : yet another combination of "≈" and "=", used to indicate equivalence or approximate equivalence
* : which can be used to represent the approach of a variable, , to a limit; like the common syntax, $\scriptstyle \lim_ y(x)$ ≐ 0
* : which is used like "≈" or "≃" in Japan, Taiwan, and Korea
* : a reversed variation of
*
*
*

Science

Approximation arises naturally in scientific experiments. The predictions of a scientific theory can differ from actual measurements. This can be because there are factors in the real situation that are not included in the theory. For example, simple calculations may not include the effect of air resistance. Under these circumstances, the theory is an approximation to reality. Differences may also arise because of limitations in the measuring technique. In this case, the measurement is an approximation to the actual value.

The history of science shows that earlier theories and laws can be ''approximations'' to some deeper set of laws. Under the correspondence principle, a new scientific theory should reproduce the results of older, well-established, theories in those domains where the old theories work. The old theory becomes an approximation to the new theory.

Some problems in physics are too complex to solve by direct analysis, or progress could be limited by available analytical tools. Thus, even when the exact representation is known, an approximation may yield a sufficiently accurate solution while reducing the complexity of the problem significantly. Physicists often approximate the shape of the Earth as a sphere even though more accurate representations are possible, because many physical characteristics (e.g.,