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Q. Show the Traditional decision analysis?
Traditional decision analysis rests on the key assumptions about the type of information available to the decision maker. Powerful Bayesian methods produce a rank of alternative strategies, and in particular, identify the optimum strategy, assuming decision maker has a well characterized system. However, we often have information about policy process different from that assumed by traditional decision analysis. For instance, while making politics we find policy process often displays regions of extreme sensitivity to a particular assumption while at the same time exhibit important regularities of the macroscopic behaviour.
An alternative to systematic policy analysis, practitioners have often used scenario based methods of decision support. This method can help decision or policy makes recognize that the future may not be an extrapolation of the past and can help interest group reach consensus on strategies even when members cannot agree on most likely future. However, even this scenario based approach does not offer two key benefits of quantitative decision analysis; particularly when applied to policy process.
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Q. Example on Uncertainty and the policy process? For example, if it is expected that current government will be replaced in upcoming election, and the next government will be
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