Decide whether to add juice sales at a coffee shop.
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Decide whether to add juice sales at a coffee shop.
States of Nature
Hgh Sales Med. Sales Low Sales
A(0.2) B(0.5) C(0.3)
A1 (sell juices) 3000 2000 -6000
A2 (don't sell juices) 0 0 0
The probabilities shown above represent the states of nature and the decision maker's degree of uncertainties and personal judgement on the occurence of each state. What is the expected payoff for actions A1 and A2 above? What would be your recommendation? Interpret the results based on practical considerations.
Bayes and emperical Bayes methods structure combining information from similiar components of information and produce efficient inferences for both individual components and shared model characteristics. For example, city specific information on the profits involved in selling a particular brand of coffee in Mumbai might be unavailable. How could a coffee shop "borrow information" from adjacent cities or other countries to employ Bayesian logic?
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E(A1) = 3000*0.2 + 2000*0.5 - 6000*0.3 = -200
E(A2) = 3000*0 + 2000*0 - 6000*0 = 0
I would recommend her to follow the option A1 based on practical considerations, even if the expected payoff is lower for A1 when compared ...
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