A project manager wants to represent the distribution of uncertainty around a risk model element. However, good data on the variability, of the risk model element has not been collected, and only…

Question

Options

• AUniform
• BBeta
• CNormal
• DLognormal

• A
  4% (2)
• B
  71% (40)
• C
  9% (5)
• D
  16% (9)

Explanation

Beta is the correct answer because it is a bounded distribution - it is defined between a minimum and maximum value - making it well-suited for situations where only those boundary estimates exist and the true shape of uncertainty is unknown. Its flexible shape parameters allow it to represent a wide range of skewed or symmetric distributions, which accurately reflects ambiguity in poorly-characterized risk elements.

Why the distractors are wrong:

• A (Uniform): While Uniform also uses only min/max, it assumes equal probability across the entire range - an overly simplistic and rarely realistic assumption for risk uncertainty.
• C (Normal): Requires a mean and standard deviation, not min/max, and is unbounded (theoretically extends to ±∞), making it inappropriate when data is sparse.
• D (Lognormal): Also requires specific statistical parameters (mean/variance of the log-transformed variable) and is unbounded on the upper end, unsuitable for bounding uncertain estimates.

Memory tip: Think "Bounded = Beta." When a risk element has a floor and ceiling but unknown shape, Beta keeps the distribution contained between those bounds while remaining flexible - unlike Normal and Lognormal, which can extend beyond realistic limits.

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