All data is entered by nodes in the tree. All following nodes in the decision tree are listed. If a node comes from a chance node then it has a non-zero probability value assigned. In the output shown below we have for each decision node the expected value and the appropriate decision and for each chance node the expected value. It is clear that the package agrees with the calculation we carried out before.
Sensitivity analysis Consider the decision tree given above.
For example, suppose the probability that we have no competition with a large plant is no longer 0.6 but is instead 0.45. To see this suppose that the probability of competition with a large plant is no longer 0.6 but is instead p. This implies that the probability that we have competition is hence 1-p. Hence if p drops below 0.3357 we would prefer a small plant to a large plant. This type of systematic sensitivity analysis can be preferable in some circumstances to simply trying different numbers and redoing the calculation to see what the effect is.