SUMMARY
The discussion centers on proving that if a set of vectors S = {u, v, w} in ℝⁿ is linearly dependent, then the transformed set {T(u), T(v), T(w)} in ℝᵐ is also linearly dependent, given that T is a linear transformation. The proof involves establishing a linear relationship among the vectors in S, represented as au + bv + cw = 0, where a, b, and c are not all zero. By applying the linear transformation T, it follows that T(au + bv + cw) = aT(u) + bT(v) + cT(w) = T(0) = 0, confirming the linear dependence of the transformed set.
PREREQUISITES
- Understanding of linear transformations in vector spaces
- Knowledge of linear dependence and independence of vectors
- Familiarity with the properties of zero vectors in linear mappings
- Basic proficiency in mathematical proofs and notation
NEXT STEPS
- Study the properties of linear transformations in depth
- Explore examples of linear dependence in various vector spaces
- Learn about the implications of linear transformations on vector space dimensions
- Investigate the relationship between linear mappings and matrix representations
USEFUL FOR
Students of linear algebra, mathematicians, and educators looking to deepen their understanding of linear transformations and vector dependencies.