This lecture covers the analysis of the column space of a matrix, distinguishing cases where the rank of the matrix equals the number of rows, leading to a pivot per row in the reduced matrix. It also discusses the dimension of the column space, the relationship between the column space and the rank of the matrix, and the implications for the solutions of linear systems.
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