What is associated with evaluating 'what-if' scenarios to test potential outcomes?

The correct answer highlights a technique specifically designed to explore various scenarios and their potential impacts, allowing decision-makers to understand the implications of different choices in a systematic way. What-if analysis allows users to change the values of variables in a model to observe how those changes affect the outcomes. This is particularly useful in decision-making processes where it is crucial to evaluate different scenarios based on varying assumptions or external conditions.

In contrast, prescriptive analysis focuses more on recommending actions based on predictive data. Statistical analysis typically involves summarizing and interpreting data without a specific focus on hypothetical scenarios. Causal analysis examines cause-and-effect relationships, which does not inherently involve altering multiple hypothetical conditions to see a range of potential outcomes.

By understanding what-if analysis, one can simulate different situations and make more informed decisions based on the range of effects these situations could generate. This makes it a valuable tool in fields such as business planning, finance, and project management.