A vector space over the real numbers is a set with an addition making it an abelian group and a scalar multiplication by satisfying, for scalars and vectors , the identities , , and . A vector subspace is a nonempty subset closed under addition and scalar multiplication; a proper vector subspace is one unequal to . A spanning set is a set whose finite linear combinations give every vector of . A basis is a linearly independent spanning set. The dimension is the number of vectors in a basis, or its cardinality when the basis is infinite.
The sum of vector subspaces and their intersection of vector subspaces are
Both are vector subspaces: addition and scalar multiplication preserve the displayed forms or simultaneous membership. The intersection of vector subspaces is never empty because .
For the two given hyperplanes, adding and subtracting their defining equations gives and . Hence
These two nonzero vectors are orthogonal, and consequently form an orthogonal basis of the intersection of vector subspaces. Put and . Direct substitution gives , . Their dot products with vanish, and . Each defining equation of or is one nonzero linear constraint in four variables, so each vector subspace has dimension three. Thus each space has the indicated orthogonal basis:
The last four vectors are nonzero and mutually orthogonal, so they are a basis of . They lie in , proving . The dimension identity is therefore verified numerically: