The Euler and improved Euler can be used to find approximate numerical solutions to differential equations of the form
[tex]y'=f(x,y)[/tex]
where the initiial point of the function is given. That is to say, it is applicable to initial value problems (although it can be applied to boundary value problems through a shooting method). I'm not sure about applications of the method to problems not related to this differential equation.
In practice, we would use a numerical method like the improved Euler method to solve a differential equation where no analytical solution exists. That is to say, there are only a handful of differential equations that can be solved through calculus and algebraic manipulation to give a closed form result.
For example, the field of computational fluid dynamics (CFD) is concerned in part with numerical solutions to the Navier-Stokes equations, which govern fluid flow. The Navier-Stokes equations are a system of nonlinear, second order, partial differential equations with variable coefficients. Here is the NS equation for the x-direction:
[tex]
\begin{align*}<br />
\rho\left(\frac{\partial u}{\partial t} + u\frac{\partial u}{\partial x} + v\frac{\partial u}{\partial y} + w\frac{\partial u}{\partial z}\right) =\\<br />
-\frac{\partial p}{\partial x} + \rho g_x + \mu\left(\frac{\partial^2 u}{\partial x^2} + \frac{\partial^2 u}{\partial y^2} + \frac{\partial^2 u}{\partial z^2}\right)<br />
\end{align}[/tex]
There are few analytical solutions to these Navier-Stokes equations. They must be solved by numerical methods in most cases.
In the case of a differential equation that cannot be solved "by hand," the numerical solution produced by method such as Euler's can provide as much information to an engineer as an exact solution. I can plot a numerical solution, numerically differentiate or integrate it, to a degree of numerical precision limited only by my time and computing power.
In practice, however, the Euler and improved Euler are not as accurate as the 4th-order Runge-Kutta method, which is another predictor-corrector "marching" method that's used more often with better results.