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Least Squares |
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Least Squares is a statistical criterion for the estimation of the
goodness of fit in correlation analysis. Least squares methods aim
to minimize the sum of squared differences between the observations
and the predictions from a model. (www6.nos.noaa.gov/coris/glossary.lasso)
Least Squares is a method for determining the line that comes nearest
to passing through a set of data points. The squares come in because
of Pythagoras' theorem about triangles. The method aims to minimize
(hence the word "least") the sum of the differences from the data
points to the line in question. (www.umass.edu/wsp/statistics/glossary/kn.html)
Least squares is a mathematical optimization technique that attempts
to find a "best fit" to a set of data by attempting to minimize the
sum of the squares of the differences (called residuals) between the
fitted function and the data. (en.wikipedia.org/wiki/Least_squares) |
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