Technical note: systematic bias in stochastic learning

Thomas Boucher and Yuchen Li

International Journal of Production Research, 2016, vol. 54, issue 11, 3452-3463

Abstract: The learning curve is a fundamental model used by engineers in cost estimating. In industry, it is typical to use the deterministic model for projecting cost, which is also suggested in standard textbooks. However, the parameters for the model are obtained from actual data, which usually come from a stochastic process. In this technical note, we investigate a particular phenomenon of the stochastic learning model that indicates that a bias may exist in the parameter estimates simply due to random behaviour in learning. The findings suggest that, on average, projections of cost from a model whose parameters are estimated from early data points are, on average, optimistic about the future cost reduction.

Date: 2016
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DOI: 10.1080/00207543.2015.1117674

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