The algebraic dual space is , the vector space of all real linear functionals. For a finite basis , define the dual basis by , so . Every linear functional satisfies
This equality follows by evaluating both sides on each vector of the basis. It proves spanning directly. If , evaluation on gives , proving linear independence without assuming a theorem on dual dimensions.
For a vector subspace , its annihilator of a vector subspace is
Extend a basis of to a basis of . Then has basis , so .
The dual map of is , . In the corresponding dual bases its matrix is the transpose of the matrix for . A matrix and its transpose have the same rank, giving . Directly,
Thus . Also every vanishes on , so . Both spaces have dimension by the preceding annihilator of a vector subspace formula and rank-nullity theorem, proving
Alternatively, a linear functional vanishing on the kernel descends to the image of and can be extended to by extending a basis.
For the infinite-dimensional polynomial ring, the coefficient functionals are linearly independent: evaluate a finite relation on each monomial. However, they do not span the algebraic dual space. The linear functional takes value one on every monomial, while any finite combination of the vanishes on every sufficiently high-degree monomial. Thus the do not form a basis of . An infinite formal sum of coefficient functionals is not a finite linear combination.

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