SUMMARY
The discussion clarifies that the nullspace of a rank 1 matrix in R^n is indeed an (n-1) dimensional subspace, often referred to as a hyperplane. For example, a 2x2 matrix with rank 1 has a nullspace that is a line in R^2, while a 3x4 matrix with rank 1 has a nullspace that is a hyperplane in R^4. The confusion arises from terminology, as the term "plane" is sometimes used informally to describe these subspaces, but it is more accurate to refer to them as hyperplanes in higher dimensions.
PREREQUISITES
- Understanding of matrix rank and its implications
- Familiarity with the concept of nullspace in linear algebra
- Knowledge of vector spaces and subspaces
- Basic proficiency in R^n notation and geometry
NEXT STEPS
- Study the properties of nullspaces in linear algebra
- Learn about the relationship between matrix rank and nullity
- Explore the concept of hyperplanes in higher dimensions
- Investigate the geometric interpretations of linear transformations
USEFUL FOR
Students of linear algebra, educators teaching matrix theory, and anyone interested in the geometric aspects of vector spaces and nullspaces.