A decision tree analysis of a problem eliminates the risks in decision making. 2) optimistic (risk prone) and pessimistic ( risk adverse) never make the same decision 3) A posterior probability is the probability of a state of nature after a test (more information) 4) The expected value of perfect information is the maximum amount a decision-maker would ever pay for additional information 5) different people should sometimes make a different deision with the same problem. Explain