In many business and engineering situations, we are interested in the impact of a single factor on the outcome or performance of a system. Ideally, we can conduct a controlled experiment to investigate. However, experimentation is often too expensive or even impossible and we have to resort to an observational approach in which data about the system is collected and subsequently analyzed in the hope of being able to isolate the effect of the factor of interest. We consider a naïve approach in which we perform a simple comparison of the observed system performance at different, known settings of the single factor of interest. Despite the fact that we ignore all the other factors which could be at any number of unknown settings when the observations were taken, this procedure turns out to be more reasonable than it might appear. We analyze this simple comparison procedure in general as well as under the assumption of several different forms of the underlying model of the system performance.
By: Ying Tat Leung; Barbara Jones
Published in: RJ10490 in 2011
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