Final answer:
The first statement is true. Any solution of the equation ATAx = Ab is a least-squares solution of the equation Ax = b. The second statement is true. A least-squares solution of the equation Ax = b is a vector x such that ||b - Ax|| ≤ ||b - A|| for all x in R. The fourth statement is true. The general least-squares problem is to find an x that makes Ax as close as possible to b. The fifth statement is true. A least-squares solution of the equation Ax = b is a vector x that satisfies Ax = b, where b is the orthogonal projection of b onto the column space of A.
Step-by-step explanation:
The first statement is true.
Any solution of the equation ATAx = Ab is a least-squares solution of the equation Ax = b. This is because the equation ATAx = Ab represents the normal equations for the least-squares problem, and its solutions are also solutions to the original equation Ax = b.
The second statement is true.
A least-squares solution of the equation Ax = b is a vector x such that ||b - Ax|| ≤ ||b - A|| for all x in R. This means that the difference between the actual value b and the predicted value Ax is minimized.
The fourth statement is true.
The general least-squares problem is to find an x that makes Ax as close as possible to b. This means that the difference between the actual value b and the predicted value Ax is minimized, which is the definition of the least-squares problem.
The fifth statement is true.
A least-squares solution of the equation Ax = b is a vector x that satisfies Ax = b, where b is the orthogonal projection of b onto the column space of A.