Which method is used to evaluate variability around the mean in risk management?

Which method is used to evaluate variability around the mean in risk management?

• A. Asymmetrical distributions
• B. Normal probability distributions
• C. Theoretical continuous distributions
• D. Measures of dispersion

Answer: (B)

A standard way to quantify how much outcomes can deviate from the expected value is to use a probabilistic model that describes how data cluster around the mean. Normal probability distributions fit this need because they are symmetric around the mean and entirely described by the mean and standard deviation, which captures the spread. This symmetry allows us to translate deviations into probabilities using z-scores and to construct confidence intervals, enabling clear risk assessments like how likely outcomes are to fall within one, two, or three standard deviations from the mean (the 68-95-99.7% rule). While other distributions may be used when data are skewed or exhibit heavy tails, the normal distribution provides a conventional, tractable framework for evaluating variability around the mean in risk management.

A standard way to quantify how much outcomes can deviate from the expected value is to use a probabilistic model that describes how data cluster around the mean. Normal probability distributions fit this need because they are symmetric around the mean and entirely described by the mean and standard deviation, which captures the spread. This symmetry allows us to translate deviations into probabilities using z-scores and to construct confidence intervals, enabling clear risk assessments like how likely outcomes are to fall within one, two, or three standard deviations from the mean (the 68-95-99.7% rule). While other distributions may be used when data are skewed or exhibit heavy tails, the normal distribution provides a conventional, tractable framework for evaluating variability around the mean in risk management.