What type of risk analysis utilizes verifiable data to assign scores to project risks?

The correct answer is quantitative risk analysis, which employs verifiable data to assign numerical scores to project risks. This type of analysis relies on statistical methods and historical data to evaluate the likelihood and potential impact of risks. By using measurable data, project managers can create a more objective and precise representation of risks, allowing for informed decision-making regarding risk responses and resource allocation.

Quantitative risk analysis often involves techniques such as Monte Carlo simulations or decision tree analysis, enabling a deeper understanding of risk interactions and their potential effects on project outcomes. This approach is particularly beneficial when there is a need for detailed analysis to support project budgeting, scheduling, or resource allocation, as it provides a clear framework for understanding the risks in a quantifiable manner.

In contrast, qualitative risk analysis typically focuses on subjective assessments based on expert judgment and experience rather than numerical data, while interconnectivity and detectability are not standard types of risk analysis recognized in project management.