Interpolation means for every node. Define the Lagrange basis polynomials
Distinctness of the nodes makes every denominator nonzero, and . Thus
is a polynomial of degree at most with the required values. If two such polynomials existed, their difference would have distinct roots while having degree at most ; the polynomial root bound makes it identically zero. Hence existence and uniqueness hold. The actual degree can be smaller than , despite the conventional name.
Multiplication by the displayed Vandermonde matrix maps the coefficient vector of a polynomial of degree at most to its vector of values at the nodes. Part (a) proves that every vector of node values is attained uniquely, so this square linear map is bijective. Therefore is invertible. Equivalently, a kernel vector would define a polynomial of degree at most with distinct roots and would have to vanish.
If is a node the error and the product both vanish, and any interior works. Otherwise put and . The function
has distinct zeros, at the nodes and at . Repeated Rolle's theorem gives a point between the extreme zeros, and therefore in , where . Since and , one gets . Substitution gives
Every derivative of order of has absolute value at most . The equally spaced nodes are symmetric about . Pair each node with ; for ,
If an unpaired middle node remains, its factor satisfies . Consequently the complete nodal product is at most . The error formula actually gives the stronger estimate
The first bound tends to zero, proving uniform convergence on the whole interval. There is no appeal to a general claim that equispaced interpolation always converges; the derivative and symmetric-product bounds are particular to this analytic function and these nodes.

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