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In the area of Human Factors and Usability research a desired output of many studies is identification of what value a specific Design Parameter should be set at to minimize customer dissatisfaction. A Customer Loss Function is a simple way to graphically display the probability customers will be dissatisfied at different levels of a given design parameter, due to a given failure mode. Many design parameters however, have two distinct but related Failure Modes (customer disatisfiers), typically representing two ends of the parameter (i.e. too much/too little; too hot/too cold; too fast/too slow). Each of these Failure modes is represented by its own unique Customer Loss Function. This paper will introduce a technique to combine these two One-Sided Loss Functions into a comprehensive Two Sided Loss Function. The mathematics behind the creation of both one sided and two sided loss functions is based on Binary Logistic Regression [1,2,3] Analysis Techniques.