Many models of engineering and scientific systems involve interactions between and among the parameters, stimuli, and physical properties. The determination of the adequacy of models for predictions and for designing experiments generally involves sensitivity studies. This is particularly true for experiments by which properties are to be estimated. Good designs mandate that the experiments be sensitive to the parameters sought with little interaction between them because such interaction generally confuse the estimation and reduce the precision of the estimates. For design purposes, analysts frequently want to evaluate the sensitivities of the predicted responses to specific variables but it the variables interact it is often difficult to separate the effects. Global sensitivity is a technique by which one can evaluate the magnitude of the interactions between multiple variables. In this paper the global sensitivity approach is applied to the human comfort equation. The aim is twofold: 1) to demonstrate the usefulness of the global sensitivity approach, 2) to increase our understanding of how human comfort is affected by activity, clothing, and environmental conditions. It is found that when occupants are uncomfortable there is little interaction and that one can predict the effects of changing several environmental conditions at once by adding the separate effects. But when occupants are comfortable there is a large interaction and the effects cannot be treated separately.

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