Actually I happened to write a short section on wikipedia about the classic bounds here. To locate the zeros of a polynomial you can also use the Rouché theorem. Also, ymay find interesting material e.g. in the book by Pólya and Szegő.

*rmk 1*: note that the above bounds of course hold for complex roots as well.

*rmk 2*: the spirit of the square root formula given in the link is: assume you have a **real** monic polynomial $p$ of degree $n$, and you just know $a_{n-1}$ and $a_{n-2}$. These numbers put a constraint (Nebenbedingung) on the size of the roots. Remember that $-a_ {n-1}= -\sum_k z_k$ and $a_{n-2}=\sum_ {j < k} z_ j z_ k$ are elementary symmetric functions of the roots $z_k:=x_k+ i y_k$. In particular, for the real parts of the roots we have
$$\sum_{k=1}^n x_k =-a_{n-1}$$
and
$$\sum_{k=1}^n x_k^2 \leq a_{n-1}^2-2a_{n-2}$$

Within these constraints, the maximum, resp. the minimum, of a real root is found maximizing, resp. minimizing $x_1;$ the method of Lagrange multipliers should easily yield (I didn't check) to (a generalization of) the given result.

Geometry of Polynomials. – J. M. Nov 2 '10 at 12:33