Proving Newton's forward difference interpolation formula

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SUMMARY

The discussion centers on proving Newton's forward difference interpolation formula, specifically the expression $$a_n = \frac{(\Delta)^n y_0}{h^n n!}$$. Participants explore the derivation of coefficients $$a_0, a_1, \ldots, a_n$$ through the use of finite differences and the relationship between the variables involved. The method of mathematical induction is suggested as a rigorous approach to validate the formula, alongside references to triangular matrices for solving the coefficients.

PREREQUISITES
  • Understanding of finite differences in numerical analysis
  • Familiarity with Newton's interpolation methods
  • Basic knowledge of mathematical induction
  • Proficiency in working with polynomial expressions
NEXT STEPS
  • Study the derivation of finite difference formulas in numerical analysis
  • Learn about mathematical induction techniques for proving formulas
  • Explore the properties of triangular matrices in linear algebra
  • Investigate applications of Newton's interpolation in computational mathematics
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Mathematicians, students in numerical analysis, and anyone interested in polynomial interpolation methods will benefit from this discussion.

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TL;DR
How to prove newtons forward difference interpolation formula using induction?
Say, $$y_n (x) = a_0 + a_1(x -x_0) + a_2(x-x_1)(x - x_0) + ... +a_n(x-x_0)(x-x_1)...(x-x_{n-1})$$
Now, $$y_0(x_0) = a_0$$
$$y_1(x_1) = a_0 + a_1(x_1 - x_0)$$
or, $$a_1 = \frac{\Delta y_0}{h}$$
Here, $$h = \frac{x_i - x_0}{i}$$
Similarly, $$a_n = \frac{(\Delta)^n y_0}{h^n n!}$$

Next substituting the values of a, we get the Newton's Forward Interpolation Formula.

It is not difficult to see that ##a_n = \frac{(\Delta)^n y_0}{h^n n!}##. But how do I prove this by induction method? Or any other rigorous way?

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