In ad-hoc and sensor networks, the location of a sensor node making an observation is a vital piece of information to allow accurate data analysis. GPS is an established technology to enable precise position information. Yet, resource constraints and size issues prohibit its use in small sensor nodes that are designed to be cost efficient. Instead, most positions are estimated by a number of algorithms. Such estimates, inevitably introduce errors in the information collected from the field, and it is very important to determine the error in cases where they lead to inaccurate data analysis. After all, many components of the application rely on the reported locations including decision making processes. It is, therefore, vital to understand the impact of errors from the applications’ point of view. To date, the focus on location estimation was on individual accuracy of each sensor’s position in isolation to the complete network. In this thesis, we point out the problems with such an approach that does not consider the complete network topology and the relative positions of nodes in comparison to each other. We then describe the existing metrics, which are used in the literature, and also propose some novel metrics that can be used in this area of research. Furthermore, we run simulations to understand the behavior of the existing and proposed metrics. After having discussed the simulation results, we suggest a metric selection methodology that can be used for wireless sensor network applications.