Changes in key variables that are introduced in a systematic way to allow for an examination of the effects that one variable has on another. For example, a firm could charge different prices in different geographical regions to assess price elasticity. In a sense, it involves doing something wrong (not charging the apparently best price) to learn. In addition to helping analysts develop forecasting models, experiments are useful in persuading decision makers to accept new forecasting methods. Whereas people are often willing to reject a new idea, they are less likely to reject a request to do an experiment. Armstrong (1982b) conducted an experiment in which subjects were asked to describe how they would gain acceptance of a model to predict the outcome of medical treatment for patients. Only one of the 16 subjects said that he would try an experiment. Armstrong then presented the situation as a role-playing case to 15 groups of health-care executives; only one group proposed an experiment, and this group was successful at implementing change while all other groups failed. Finally, Armstrong gave 14 groups instructions on how to propose experiments in this situation; of these, 12 were successful at gaining acceptance in role-playing exercises.