The experimental design and subsequent analysis of the data collected from experimentation are tightly coupled. This paper considers techniques for the analysis of data collected from experimentation based on a locating array. Because locating arrays can be highly unbalanced, new analysis techniques are required. In order to cope with noise in the measured performance data, a search is conducted to identify the significant parameters and interactions that impact the data. A novel “heavy hitters” bounded breadth-first search (BFS) tree algorithm is proposed for analysis. It is used to validate data collected from large-scale experimentation with a physical wireless network testbed and a wireless network simulator, varying 24 and 75 parameters, respectively.