Decision Trees

• Decision trees are models used to guide decision making by analyzing the probabilities of different outcomes.
• A decision tree consists of options, possible outcomes, probabilities, and expected returns.
• Expected value is calculated by multiplying the probability by the return for each outcome.
• Net gain is calculated by subtracting the initial cost from the expected value.

Decision trees are models used to guide decision making by analyzing the probabilities of different outcomes. A typical decision tree starts with a decision and presents various options with their associated costs and probabilities of success or failure. The expected value for each option is calculated by multiplying the probability by the return. The net gain is then determined by subtracting the initial cost from the expected value. Decision trees provide a visual representation of possible outcomes and use quantitative forecasting to inform decision making. However, they should be used in conjunction with qualitative factors and are reliant on the accuracy of the forecast and data provided. In the example given, investing in new machinery is the recommended course of action, despite the higher cost and potential for loss. Ultimately, decision trees offer a structured approach to decision making but should be used alongside other considerations.