This **crossword clue** is for the definition: *Certain.*

it’s A 7 letters **crossword puzzle definition**.

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## Possible Answers: **Sure**.

Last seen on: Daily Celebrity Crossword – 9/13/18 Top 40 Thursday

### Random information on the term “Certain”:

Related concepts and fundamentals:

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

The word approximation is derived from Latin approximatus, from proximus meaning very near and the prefix ap- (ad- before p) meaning to.[1] 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.[2] 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.

### Random information on the term “Sure”:

In econometrics, the seemingly unrelated regressions (SUR)[1]:306[2]:279[3]:332 or seemingly unrelated regression equations (SURE)[4][5]:2 model, proposed by Arnold Zellner in (1962), is a generalization of a linear regression model that consists of several regression equations, each having its own dependent variable and potentially different sets of exogenous explanatory variables. Each equation is a valid linear regression on its own and can be estimated separately, which is why the system is called seemingly unrelated,[3]:332 although some authors suggest that the term seemingly related would be more appropriate,[1]:306 since the error terms are assumed to be correlated across the equations.

The model can be estimated equation-by-equation using standard ordinary least squares (OLS). Such estimates are consistent, however generally not as efficient as the SUR method, which amounts to feasible generalized least squares with a specific form of the variance-covariance matrix. Two important cases when SUR is in fact equivalent to OLS are when the error terms are in fact uncorrelated between the equations (so that they are truly unrelated) and when each equation contains exactly the same set of regressors on the right-hand-side.