why is it easier to use the gaussian elimination method than cramer's rule when solving linear systems
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OpenStudy (skullpatrol):
Any ideas?
OpenStudy (skullpatrol):
What do you mean by "easier"?
OpenStudy (anonymous):
i know that it is a simpler to find the variables this way
OpenStudy (anonymous):
you can use backsubstitution
OpenStudy (anonymous):
it is better than cramer's rule when you have bigger matrixes, its homework question
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OpenStudy (skullpatrol):
Yes, Gauss was a master at solving problems by using the FEWEST steps possible.
OpenStudy (anonymous):
cramer definitely uses more steps and gets more complicated with bigger matrixes
OpenStudy (skullpatrol):
Unfortunately, he also used the fewest words possible in this work.
OpenStudy (anonymous):
yes not enough explanation
OpenStudy (skullpatrol):
But he is, historically considered the greatest mathematician.
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OpenStudy (anonymous):
is that true?
OpenStudy (anonymous):
Sometimes, Cramer's rule must be applied to solve the problem. It is more difficult because it need the augmented matrix must be a square one and its determinant \(\neq\) 0. While Gaussian can apply to any of them.