Math Problem Statement

The following data represents the function x f (x)  e , x 1 1.5 2 2.5 3 f (x) 2.7183 4.4817 7.3891 12.1825 20.0855 Estimate the value of f (1.75) by using the Newton’s forward difference interpolation. Obtain a bound on the error at x 1.75 .

Solution

To estimate the value of f(1.75)f(1.75) using Newton's forward difference interpolation, we'll follow these steps:

Step 1: Tabulate the given data

The data provided is:

x & f(x) = e^x \\ \hline 1.0 & 2.7183 \\ 1.5 & 4.4817 \\ 2.0 & 7.3891 \\ 2.5 & 12.1825 \\ 3.0 & 20.0855 \\ \end{array}$$ ### Step 2: Forward differences We construct the forward difference table. Denote the first forward difference by $$\Delta f(x)$$, the second by $$\Delta^2 f(x)$$, and so on. $$\begin{array}{c|c|c|c|c} x & f(x) & \Delta f(x) & \Delta^2 f(x) & \Delta^3 f(x) \\ \hline 1.0 & 2.7183 & 1.7634 & 1.1440 & 0.0486 \\ 1.5 & 4.4817 & 2.9074 & 1.1926 & \\ 2.0 & 7.3891 & 4.7934 & \\ 2.5 & 12.1825 & 7.9030 & \\ 3.0 & 20.0855 & \\ \end{array}$$ ### Step 3: Newton's forward difference formula Newton's forward difference formula for interpolation is: $$P(x) = f(x_0) + p\Delta f(x_0) + \frac{p(p-1)}{2!} \Delta^2 f(x_0) + \frac{p(p-1)(p-2)}{3!} \Delta^3 f(x_0) + \cdots$$ where $$p = \frac{x - x_0}{h}$$, $$h$$ is the difference between consecutive $$x$$-values (in this case $$h = 0.5$$), and $$x_0 = 1.0$$. For $$x = 1.75$$: $$p = \frac{1.75 - 1.0}{0.5} = 1.5$$ Now, we substitute into the interpolation formula: $$P(1.75) = f(1.0) + p \Delta f(1.0) + \frac{p(p-1)}{2!} \Delta^2 f(1.0) + \frac{p(p-1)(p-2)}{3!} \Delta^3 f(1.0)$$ Substituting the values: $$P(1.75) = 2.7183 + 1.5(1.7634) + \frac{1.5(0.5)}{2!} (1.1440) + \frac{1.5(0.5)(-0.5)}{3!} (0.0486)$$ ### Step 4: Calculation $$P(1.75) = 2.7183 + 2.6451 + 0.4290 - 0.0061$$ $$P(1.75) \approx 5.7863$$ ### Step 5: Error bound The formula for the error bound in Newton's forward difference interpolation is: $$E(x) = \frac{f^{(n+1)}(\xi) (x - x_0)(x - x_1) \cdots (x - x_n)}{(n+1)!}$$ Here, the maximum value of $$f^{(4)}(x)$$ (since the 4th forward difference is small) for $$f(x) = e^x$$ can be estimated as the maximum value of $$e^x$$ on the interval $$[1, 3]$$. Since $$e^x$$ is increasing, the maximum value is at $$x = 3$$, which gives $$e^3 \approx 20.0855$$. The error bound can be approximated as: $$E(1.75) \approx \frac{20.0855 (1.75 - 1.0)(1.75 - 1.5)(1.75 - 2.0)(1.75 - 2.5)}{4!}$$ $$E(1.75) \approx \frac{20.0855 \times 0.75 \times 0.25 \times (-0.25) \times (-0.75)}{24}$$ $$E(1.75) \approx \frac{20.0855 \times 0.03515625}{24} \approx 0.0294$$ ### Final result: The estimated value of $$f(1.75)$$ using Newton's forward difference interpolation is approximately **5.7863**. The bound on the error is approximately **0.0294**. --- Would you like more details or clarifications on this method? ### Related Questions: 1. How is Newton's backward difference interpolation different from the forward difference? 2. What are other methods for polynomial interpolation? 3. How does the step size $$h$$ affect the accuracy of Newton’s interpolation? 4. Can you derive the error term for higher-order Newton interpolations? 5. What is the difference between Lagrange interpolation and Newton's method? **Tip:** When working with interpolation, always ensure the spacing between $$x$$-values (step size) is consistent for applying Newton’s method effectively.

Ask a new question for Free

By Image

Drop file here or Click Here to upload

Math Problem Analysis

Mathematical Concepts

Numerical Methods
Interpolation
Exponential Functions
Error Bound

Formulas

Newton’s forward difference interpolation formula: P(x) = f(x_0) + pΔf(x_0) + (p(p-1)/2!) Δ^2f(x_0) + (p(p-1)(p-2)/3!) Δ^3f(x_0)
Error bound formula: E(x) = f^{(n+1)}(ξ) (x-x_0)(x-x_1)...(x-x_n)/(n+1)!

Theorems

Newton's Forward Difference Theorem
Error Bound Theorem in Polynomial Interpolation

Suitable Grade Level

Undergraduate - Numerical Methods Course