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For an explicit basis extension in ${\mathbb{R}}^2$, start with $A=\{u\}$, where $u=(1,1)$. Its linear span is the line $y=x$. Adding $w=(1,-1)$ preserves linear independence, because $w$ is outside that line, and gives a basis. Every vector has the finite linear combinationThe vector $2u=(2,2)$ cannot be added while preserving linear independence: it is already in the linear span. Many choices outside the line work, so maximality does not select a unique basis.

For a finite-dimensional vector space with a supplied finite spanning set, a greedy algorithm scans the list, retaining each vector precisely when it is outside the linear span of those already retained. Starting with a linearly independent $A$, the same scan adjoins only the needed vectors. Retained vectors remain linearly independent, and every skipped vector is in the final linear span, so the result is a basis containing $A$. Finite reasoning needs no axiom of choice.

For an arbitrary vector space, this finite stopping argument is unavailable. Accepting Zorn's lemma asserts existence of a maximal element once every chain in a partial order has an upper bound; it supplies no general computational recipe. Over ZF, Zorn's lemma, the axiom of choice and the well-ordering theorem are equivalent. Particular infinite vector spaces can still have explicit bases, such as $1,x,x^2,\dots$ for the vector space of univariate polynomials over a specified field; infinity alone does not force a nonconstructive argument.^[ref]

Suppose for contradiction that the vector space of univariate polynomials $P$ were complete in the given norm. For $n\ge 0$, letEach $P_n$ is finite-dimensional and therefore closed by the fact that a finite-dimensional subspace is closed. It is a proper linear subspace of $P$, so it has empty interior: if a linear subspace contained any open ball, translation and scalar multiplication would make it contain every vector. Hence every $P_n$ is a nowhere dense set.

But every polynomial has finite degree, soThis writes the supposed complete metric space $P$ as a countable union of nowhere-dense closed subsets, contradicting the Baire category theorem. Thus no norm can make $P$ complete. Equivalently, this is the countable-basis obstruction that a Banach space has uncountable Hamel dimension.

The polynomial $p_n$ interpolates $f$ at the interpolation nodes whenFor distinct interpolation nodes, define the Lagrange cardinal polynomialsThe denominators are nonzero, each polynomial degree is at most $n$, and ${\ell }_i(x_j)={\delta }_{ij}$, with ${\delta }_{ij}$ the Kronecker delta. Thereforeis a Lagrange interpolation polynomial belonging to the vector space of univariate polynomials ${\Pi }_n$, and it has all the required sampled values.

If $r_n\in {\Pi }_n$ also works, $p_n-r_n$ has $n+1$ distinct roots of a polynomial while its polynomial degree is at most $n$. The root bound for a polynomial forces it to be the zero polynomial, proving uniqueness. The phrase “degree $n$” denotes the allowed maximum; the actual polynomial degree may be smaller. No continuity assumption is needed merely to construct the interpolation polynomial from these finitely many values.

For each interpolation node define the Lagrange cardinal polynomialAll denominators are nonzero because the interpolation nodes are distinct. Each polynomial has polynomial degree at most $n$, and ${\ell }_j(x_i)={\delta }_{ij}$, where ${\delta }_{ij}$ is the Kronecker delta. Consequently the linear combinationbelongs to the vector space of univariate polynomials ${\Pi }_n$ and has the required values. This proves existence of the Lagrange interpolation polynomial.

For uniqueness, suppose $p_n$ and $r_n$ both work. Their difference is a polynomial of polynomial degree at most $n$ with $n+1$ distinct roots of a polynomial. The root bound for a polynomial forces $p_n-r_n$ to be the zero polynomial.

The seven supplied values follow $f_i=i^2+1$. The quadratic polynomial $x^2+1$ belongs to ${\Pi }_6$ and takes all seven values, so uniqueness givesThe subscript bounds the polynomial degree; it does not require polynomial degree exactly six.