The sensitivity of linear systems is a question of great interest in numerical analysis. Sensitive systems can lead to untrustworthy results. Traditionally, the condition number,, is used to measure the sensitivity of a system. However, in many scenarios  can be large when the solution is known to be accurate. Alternatively, we can use the effective condition number, e. For a given linear system, the e often gives a much better bound on error. This is especially true in numerical PDE’s. For example, it can be shown for Poisson’s equation on the unit square solved through the finite difference method (FDM) that e=O(1)and=O(h2), where h is the maximal mesh spacing. This talk will discuss e and its utility to numerical PDE’s.