STATISTICAL ATTRIBUTES OF THE POWER LEARNING-CURVE MODEL

A learning curve is a well known tool which describes the relation bet ween the performance of a task and the number of repetitions of that t ask. A learning curve model may be used as a prediction tool in variou s applications of operations planning and control. Previous models hav e treated learning as a deterministic phenomenon, whereas this paper a ddresses its stochastic nature and treats learning as a random process . Exact expressions of the variance, of the coefficient of variation a nd of the probability density function of the performance, expressed a s a function of the number of repetitions of a task, are derived for t he power model. Mathematical analysis reveals that the coefficient of variation is independent of the number of repetitions. The probability density function type was also found to be independent of the number of repetitions. Analysis of actual learning data validated the theoret ical findings. These findings enable improved forecasting of future pe rformance by using a stochastic rather than a deterministic estimation .