The terms given in this glossary can be applied for business applications and this primer. Other applications such as medicine, artificial intelligence, or general problem solving may use non-monetary value calculations.
Baseline: A standard state or specific value, also called a control in some fields, used to compare experimental results.
Branch: A particular decision alternative or chance outcome. A branch representing a decision alternative emanates from a decision node. A chance branch (chance outcome) emanates from a chance node.
Branch path: A series of connected branches leading from a decision node through any given endpoint.
Chance branch (chance outcome): One of the possible outcomes emanating from a chance branch. In a decision tree two or more chance branches are lines drawn to the right from a chance node.
Chance node, or chance event node: A node that identifies an event in a decision tree where a degree of uncertainty exists. A chance node represents at least two possible outcomes. Small circles in a decision tree show chance nodes.
Cost: A monetary expense required for a particular decision alternative or that must be paid at a particular chance outcome. Typical cost examples are investments (on decision branches) and penalties (on chance branches). In this primer, investment costs are shown as negative values.
Data mining: A process that uses software to explore information stored in databases for trends and patterns.
Decision alternative: A choice between two or more decision alternatives. In a decision tree, a branch emanating from a decision node represents each decision alternative.
Decision branch: A a particular decision alternative. In a decision tree, two or more decision branches are lines drawn to the right from a decision node.
Decision node: A location on a decision tree where a decision between at least two possible alternatives can be made. Decision nodes are indicated by small squares in a decision tree.
Decision strategy: A particular branch path in a decision tree and includes all the decisions and chance events along that branch path. A decision tree generally includes two or more possible decision strategies. One decision strategy is generally found to be the “preferred decision strategy” since decision strategies can be compared by computing their respective expected values (EV).
Decision tree: A diagram used to describe decision alternatives and chance events.
Decision tree analysis: The process of evaluating alternative decision alternatives emanating from the root node. The analysis requires calculating and then comparing expected values. The analysis can also involve making adjustments to probabilities and payoff values to determine how changes to those values may affect expected values.
Decision tree notation: A set of graphic symbols and conventions used to describe elements in a decision tree. Commonly used decision tree notation includes decision nodes, chance nodes, endpoints, branches, and double-hatch marks.
Dependent uncertainty: A condition whereby a chance event depends on a prior chance event. For example, if the chance of event “B” will occur depends on the chance that event “A” will occur, then some of the uncertainty associated with “B” depends on “A.” In a decision tree, a chance node that is directly connected to another chance node indicates a dependent uncertainty.
Double-hatch marks: A pair of small lines that are placed over a branch to indicate that particular branch is not to be considered in an expected value calculation.
Endpoint: A node that terminates a branch (and also a branch path). In a decision tree, an endpoint is drawn as a small triangle, with one apex connected to the branch. The endpoint is the location where a payoff value is identified. A decision tree is “terminated” when all the branch paths result in an endpoint with a payoff value.
Expected value: A criterion for making a decision. Expected value is a mathematical term that combines the payoffs and probabilities of possible chance outcomes for a decision alternative.
Technical note: The expected value represents the “average payoff value” expected if a decision were to be repeated many times. The term depends on the relative likelihood of events occurring if the decision were repeated many times while the circumstances remain constant. Many real-world decisions do not have the advantage of being repeatable. Nevertheless, probabilities can still be assigned to outcomes based on information from expert judgment and other means of risk analysis. Such methods are beyond the scope of this primer. For the purposes of this primer assume that the examples use realistic probabilities from reliable sources.
EV: An abbreviation for expected value.
Investment cost: The monetary amount to be allocated at a decision branch. In this primer, investment costs are shown as negative values.
Node: A symbol in a decision tree indicating decision alternatives, chance outcomes, or a branch termination.
Payoff, or payoff value: A monetary amount that will be earned at the conclusion of a branch path. Payoff, also called net profit or return on investment, is the difference between the costs and the gross revenue earned. A positive payoff is equivalent to a positive net profit. A negative payoff is equivalent to a net loss.
Rollback, or rollback calculation: The process of successively calculating expected value by beginning at an endpoint and calculating subsequent expected values back towards the root node.
Return on investment (ROI): Another term for payoff (or net profit or loss).
Root node: The initial decision node from which a decision tree is established.
Sequential decision: A situation in which more than one decision may be required before a decision tree can be terminated. All but the simplest decision trees contain sequential decisions.
Spreadsheet: A software application used for managing multiple calculations. Microsoft Excel® is the leading spreadsheet application on Windows and Mac OS operating systems.
Termination node: Another term for endpoint.