![]() Many authors have obtained partial solutions for this problem as discussed by Womer and Marcotte and Wonnacott and Wonnacott, which result in generalized least squares algorithms to solve restrictive cases. Camm, Gulledge, and Womer, and Womer and Marcotte provide excellent applied examples of these concerns. Throughout the literature authors have consistently discussed the suspicion that regression results were less than satisfactory when the independent variables were correlated. ![]() The advantage of using MS Excel is its availability and transparency (the user is responsible for most of the details of how a problem is solved). In this note, we demonstrate with illustrations two different ways that MS Excel can be used to solve Linear Systems of Equation, Linear Programming Problems, and Matrix Inversion Problems. Linear System of Equations, Matrix Inversion, and Linear Programming Using MS ExcelĮRIC Educational Resources Information Center
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