Polynomials are one of the most commonly used types of curves in regression. The applications of the method of least squares curve fitting using polynomials are briefly discussed as follows. To obtain further information on a particular curve fitting, please click on the link at the end of each item.
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The LeastSquares Line: The leastsquares line method uses a straight line to approximate the given set of data, , , ..., , where . See complete derivation.
The LeastSquares Parabola: The leastsquares parabola method uses a second degree curve to approximate the given set of data, , , ..., , where . See complete derivation.
The LeastSquares m^{th} Degree Polynomials: The leastsquares m^{th} degree Polynomials method uses m^{th} degree polynomials to approximate the given set of data, , , ..., , where . See complete derivation.
Multiple Regression LeastSquares: Multiple regression estimates the outcomes which may be affected by more than one control parameter or there may be more than one control parameter being changed at the same time, e.g., . See complete derivation.
