If A has linearly independent columns (say n columns), then the first n columns of Q form an orthonormal basis for the column space of A.
The methods given for solving nonsingular linear systems of eqations relied upon factoring the coefficient matrix into a product of simpler matrices for which it is easy to solve a linear system.
It also had to give back the northern part of Schleswig-Holstei…It is a very subjective question.
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Orthogonal matrices are important in least squares methods, because multiplying a vector by an orthogonal matrix does not change its two-norm. Given that A is m × n and Q is orthogonal, what are the dimensions of R?
Do not proceeed further until you have answered that question.
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