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Using simulated experience to make sense of big data
(Massachusetts Institute of Technology, 2015)
Simulated experience can help companies communicate data analysis results to decision makers. Analysts' conclusions have been found to be different from what decision makers understand. Meanwhile, complex statistical ...
The golden rule of forecasting: objections, refinements, and enhancements
(Elsevier, 2015-08)
In providing a “golden rule” for forecasting, Armstrong, Green, and Graefe (this issue) raise aspirations that reliable forecasting is possible. They advocate a conservative approach that mainly involves extrapolating from ...
Communicating forecasts: the simplicity of simulated experience
(Elsevier, 2015-08)
It is unclear whether decision makers who receive forecasts expressed as probability distributions over outcomes understand the implications of this form of communication. We suggest a solution based on the fact that people ...
The two settings of kind and wicked learning environments
(Association for Psychological Science, 2015-10)
Inference involves two settings: In the first, information is acquired (learning); in the second, it is applied (predictions or choices). Kind learning environments involve close matches between the informational elements ...
Fooled by experience
(Harvard Business Publishing, 2015-05)
We interpret the past—what we’ve experienced and what we’ve been told—to chart a course for the future. It seems like a reasonable approach, but it could be a mistake. The problem is that we view the past through filters ...
Providing information for decision making: Contrasting description and simulation
(Elsevier, 2015-09)
Providing information for decision making should be like telling a story. You need to know, first, what you want to say; second, whom you are addressing; and third, how to match the message and audience. However, data ...
Learning from experience in nonlinear environments: Evidence from a competition scenario
(Elsevier, 2015-09)
We test people’s ability to learn to estimate a criterion (probability of success in a competition scenario) that requires aggregating information in a nonlinear manner. The learning environments faced by experimental ...
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