probability-scenario-weighting

Scenario weighting assigns calibrated probabilities to mutually exclusive scenarios by forcing probabilities to sum to 100% and validating them through bet acceptance checks, converting vague uncertainty into decision-ready risk assessments.

Scenario analysis quantifies uncertainty by enumerating mutually exclusive outcomes, assigning probability distributions, and extracting the highest-probability and highest-impact implications to drive risk mitigation and planning decisions.

Scenario decomposition enumerates mutually exclusive and collectively exhaustive outcomes, assigns explicit likelihoods to each, and identifies key drivers to model real uncertainty instead of vague optimism in forecasting tasks.

Probability calibration identifies the single most useful information to gather next by extracting key drivers for each scenario and determining what would most change your belief to reduce uncertainty before making a decision.

Probabilities must sum to 100% to ensure scenarios are mutually exclusive and collectively exhaustive, creating a valid probability distribution over outcomes that enables accurate calibration via bet acceptance checks.

Use probability scenario weighting when planning, forecasting, or risk management tasks involve significant uncertainty that must be represented as a probability distribution over multiple mutually exclusive outcomes rather than a single prediction.