a.	CoffeeTime is considering selling juices along with its other products. 
                	        	States of Nature
 	 	      High 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 (e.g., manager) degree of uncertainties and personal
judgment on the occurrence 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.

b.         Bayes and empirical Bayes (EB) methods structure combining
information from similar 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 CoffeeTime ?borrow information? from adjacent
cities or other countries to employ Bayesian logic?

I'm fairly certain this isn't too difficult but I'm not sure how to
proceed any help would be appreciated.