Rigorous analysis and evaluation of real implemented robotic systems for intelligent tasks are rarely performed. Such systems are often extremely complicated, depending not only on 'interesting' theoretical parameters and models, but on many assumptions and constants which may be set almost arbitrarily. We view all task implementations as particular parameterizations of the task goals they represent. Through fractional factorial experiments we establish the statistically significant parameters and parameter interactions for a 'sensorless' model-based push-orienting task. This type of analysis is a necessary step to understanding integrated intelligent systems. It reveals aspects of system implementations which cannot easily be predicted in advance, and gives a clear picture of the task requirements, given the strengths and weaknesses of the observed system.