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 ?
Linear regression using ordinary least squares on log-transformed data and non-linear regression were used to compare the results.
The main problem Ordinary Least Squares should solve is that when observation data of samples have already acquired Y and X, the unclear mapping relation between X and Y is still to be found.
The data analyses of the particular study consist of an Ordinary Least Squares (OLS) regression technique diagnostic tests of several types have also been performed to test the data before doing the OLS regression.
To facilitate this exploration of why researchers might disregard complex sample design when completing multivariate analyses, logistic regression and ordinary least squares (OLS) regression models typically found in the health insurance literature were estimated.
In a situation, where the series are cointegrated at first difference 'I(1)', Fully modified ordinary least squares (FMOLS) is suitable for estimation.
The possible methods include Ordinary Least Squares (OLS), fixed effects model and random effects model with the selection criteria by Hausman test.
The regressions were performed using ordinary least squares (OLS) allowing for within-state correlation in errors to control for repeated observations from the same state.
A log log ordinary least squares multiple regression model was estimated as a demand function of milk.
Using Ordinary Least Squares regression analysis, the study found that a grade incentive to complete assignments boosted the exam performance of academically average freshman students but not those who were academically above or below average, or of any other class standing.
This rush seems to be based on the assumption that HLM might yield substantively different findings than those from studies based on ordinary least squares (OLS) regression analyses.
Topics included Organising Data Analysis & Recoding, Missing Data & Scale-Building, Basic Hypothesis Testing & Introduction to Ordinary Least Squares Regression, as well as Ordinary Least Squares Regression & Secrets to Data Presentation.