Euler's method approximates a solution curve by taking small linear steps. Starting from the initial condition (x_0, y_0), compute the slope f(x_0, y_0), step forward by h to get x_1 = x_0 + h and y_1 = y_0 + h * f(x_0, y_0), then repeat. Smaller step sizes give better approximations. Organize each iteration in a table showing x_n, y_n, f(x_n, y_n), and y_{n+1}.
- Update rule: y_{n+1} = y_n + h * f(x_n, y_n), where h is the step size and f(x_n, y_n) is the slope at the current point.
- Step size h: The horizontal distance between successive approximation points; smaller h reduces error but requires more steps.
- Overestimate vs. underestimate: If the solution is concave up, Euler's method underestimates; if concave down, it overestimates, because it uses the slope at the left endpoint of each step.
Use Euler's method with h = 0.5 to approximate y(1) for dy/dx = x + y with y(0) = 1. Show two steps in a table.
| Concavity of true solution | Euler approximation error direction |
|---|
| Concave up | Underestimate |
| Concave down | Overestimate |