The properties of the unique solution of the system AX=B depend on the matrix of the system. That is, it depends only on the coefficients on the left side. RHS configuration is not the issue.
The method of least squares is an important statistical technique practiced to find the regression line or the best fit line for a particular pattern. This procedure is described by an equation with specific parameters. The method of least squares is used liberally in analysis and regression. In regression analysis, this method is a standard approach to approximating a system of equations using more equations than unknowns.
The least squares method actually defines a solution to minimize the resulting sum of squares or error for each equation. Find the formula for the sum of squared errors to help find the variation in the observed data.
The least squares method is often used in data fitting. A best fit result is assumed to reduce the sum of squared errors or residuals reported as the difference between the observed or experimental values and the corresponding fitted values in the model.
Linear System of Equation:
A system of linear equations (or linear system) is a collection of one or more linear equations involving the same variables.
A linear system of three variables determines the collection of levels. Intersection is the solution.
For example,
3x + 2y -z =1 , 2x - 2y + 4z =-2
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