Method of least squares vs Method of the least sum of squares

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Method of least squares is the most popular phrase on the web. 

Method of the least sum of squares

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Method of least squares

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Some examples and use cases from the internet:

  • This can be done graphically or by dividing the residual sum of squares into "lack of fit" and "pure error components" and performing a significance test for lack of fit.
  • Note that if multiple maximum values are found, the denormalization speed (ndenorm) should be taken as the lowest speed of all points with the same maximum sum of squares.
  • VarRed is considered as an index of the waveform fit between observed and synthetic seismograms and is equal to the sum of squares of the difference in amplitude normalized by the observed waveforms (100% is best).
  • Controlling for baseline differences by using an analysis of covariance with a Type III sums of squares
  • Calculate sum of squares of each row in a matrix
  • information about quality criteria for this method (e.g. correlation coefficient, error sum of squares, etc.),
  • The DEVSQ() function calculates the sum of squares of deviations.
  • This involves comparing the squared maximum duplicate range with the sum of square ranges.
  • In this case, the use of complex computer programmes is not required, if the triglyceride combinations used in Table 2 are applied and the factors redetermined by using the method of least squares.
  • Scale factor is generally evaluated as the slope of the straight line that can be fitted by the method of least squares to input
  • Scale factor is generally evaluated as the slope of the straight line that can be fitted by the method of least squares to input
  • All exhaust emissions results shall be plotted as a function of the running distance on the system rounded to the nearest kilometre and the best fit straight line fitted by the method of least squares shall be drawn through all these data points.
  • The calibration curve is calculated by the method of least squares.
  • output data obtained by varying the input cyclically over the input range.
  • The usual method for doing this is the method of least squares.
  • The method of least squares shall be used with the best fit equation having the form:

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