Probability distributions are frequently used in Perform Quantitative Risk Analysis. Which of these is not a valid example of such a distribution?
A. Sigma distribution
B. Logarithmic distribution
C. Triangular distribution
D. Beta distribution
Answer A –
Explanation - The response 'Sigma distribution' is not a valid distribution. Continuous probability
distributions represent the uncertainty in values, such as durations of schedule activities and
costs of project components. Triangular, Beta, Logarithmic, Normal and Uniform
distributions are other examples of commonly used distributions. [PMBOK 5th edition, Page
337] [Project Risk Management]
http://mathworld.wolfram.com/Logarithmi ... ution.html
If you see skewedness of data especially in the right tail in the normal distribution then it is due to large number of positive outliers. In such case you would plot a log normal distribution of the same data so that you would get a closer to normal curve (of course Log normal distribution is not symmetrical like normal distribution ) as log value of any number/outlier is smaller their actual value.
Example: real estate properties value, oil prices, stock prices etc.
Hope this helps
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