least squares

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least squares

pl.n. Statistics
A method of determining the curve that best describes the relationship between expected and observed sets of data by minimizing the sums of the squares of deviation between observed and expected values.

least squares

n
(Mathematics) a method for determining the best value of an unknown quantity relating one or more sets of observations or measurements, esp to find a curve that best fits a set of data. It states that the sum of the squares of the deviations of the experimentally determined value from its optimum value should be a minimum

least′ squares′


n.
a statistical method of estimating values from a set of observations by minimizing the sum of the squares of the differences between the observations and the values to be found.
Also called least′-squares′ meth`od.
[1860–65]
ThesaurusAntonymsRelated WordsSynonymsLegend:
Noun1.least squares - a method of fitting a curve to data points so as to minimize the sum of the squares of the distances of the points from the curve
statistics - a branch of applied mathematics concerned with the collection and interpretation of quantitative data and the use of probability theory to estimate population parameters
statistical method, statistical procedure - a method of analyzing or representing statistical data; a procedure for calculating a statistic
References in periodicals archive ?
Least-squares analysis is not valid when addressing a performance improvement goal stated as "95 percent of patients have less than 10 days between first contact and first treatment.
Least-squares analysis of data with unequal subclass numbers.
The frequency counts of attacked tube caps (those with screen loss, wall damage, or both) were analyzed by weighted least-squares analysis of variance using the SAS Institute's CATMOD procedure with a significance level of [alpha] = 0.
Some of these factors can be minimized by procedural technique, such as choosing optimum indicator sampling parameters, achieving precise transducer alignment, maintaining of machine weight changing and motion inhibiting mechanisms, and properly selecting the order of fit for the least-squares analysis.
A linear least-squares analysis of these data yields the equation y = 0.
by nonlinear least-squares analysis to the A1c mass value in the dilution analysis (STATA Release 6, College Station, TX).
We generally assume that least-squares analysis is sufficient and indeed it is often so.

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