Abstract
Decision making is inherently forward-looking. Data analysis can be very valuable in illuminating the prospects for various alternatives. However, there is little understanding of the limitations of using historical data and analysis for decision making, or of where and how it needs to be supplemented using subjective, Bayesian probabilities. This chapter presents why subjective probabiities are needed and how to do a good job of obtaining them. These skills are critical for making better decisions.
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Although it is beyond the scope of this text, I have taken an in-depth look at where the securitization boom went bust. For our purposes here, I will simply note that I have attended presentations by senior personnel at one of the major rating agencies describing in detail their analyses by PhD statisticians and economists which failed utterly at predicting the prospects for the housing market and the securities based on them. In the end, the key questions for any uncertainty quantification and risk management methods are: Is it working? How do you know? See Hubbard, Douglas W., The Failure of Risk Management. Wiley 2009: Hoboken, NJ.
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I am not presently aware of a source to purchase these wheels, and have needed to have them specially made when I run out. If you know of a source, please drop me an email.
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© 2016 Springer International Publishing Switzerland
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Celona, J. (2016). Elicit Probabilities. In: Winning at Litigation through Decision Analysis. Springer Series in Operations Research and Financial Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-30040-5_5
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DOI: https://doi.org/10.1007/978-3-319-30040-5_5
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Publisher Name: Springer, Cham
Print ISBN: 978-3-319-30038-2
Online ISBN: 978-3-319-30040-5
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