There has been much concern about making the curriculum for engineering statistics more relevant to the needs of industry. One proposed solution is to include decision risk analysis in the curriculum. However, the current coverage of decision risk analysis in statistics textbooks is either nonexistent or very introductory. In part, this reflects the fact that decision risk analysis, as currently taught, relies on the complex notion of a utility function.<br>Recent research in decision theory suggests a way of comprehensively and rigorously discussing decision theory without using utility functions. In this new approach, the decision risk analysis course focuses on making decisions so as to maximize the probability of meeting a target. This allows decision theory to be integrated with reliability theory. This course would be more comprehensive than the conventional introductory treatment of decision theory and no more difficult to teach. In addition, integrating decision theory with reliability theory facilitates its incorporation in curricula that currently exclude decision theory.
The CAUSE Research Group is supported in part by a member initiative grant from the American Statistical Association’s Section on Statistics and Data Science Education