SUMMARY
To prove that the matrix A^TA is invertible when A is an m x n matrix with linearly independent columns, one must consider the implications of linear independence on the rank of A. Since the columns of A are linearly independent, the rank of A equals n, which in turn implies that the rank of A^TA is also n. Consequently, A^TA is a square matrix of full rank, confirming its invertibility.
PREREQUISITES
- Understanding of linear independence in matrices
- Familiarity with matrix multiplication and properties
- Knowledge of matrix rank and its implications
- Basic concepts of linear transformations
NEXT STEPS
- Study the properties of matrix rank and its relationship to invertibility
- Learn about the implications of linear independence in higher dimensions
- Explore the concept of orthogonality in relation to A^TA
- Investigate the Singular Value Decomposition (SVD) and its applications
USEFUL FOR
Students of linear algebra, mathematicians, and anyone involved in theoretical mathematics or applied fields requiring matrix analysis.