A Review of Activity Time Distributions in Risk Analysis <s> 5) The Lognormal Distribution <s> The original PERT formulae [5] employ the mode and endpoints to estimate the mean and standard deviation of subjective probability distributions. Though widely-used, they have met with criticism for their inaccuracy, and for their being limited to the beta distribution when there is no a priori reason why the distribution should be beta ([4], [6]). This note presents alternative, accurate and relatively distribution-free formulae for estimating the means and standard deviations of subjective probability distributions. <s> BIB001 </s> A Review of Activity Time Distributions in Risk Analysis <s> 5) The Lognormal Distribution <s> Based on theoretical arguments and empirical evidence we advocate the use of the lognormal distribution as a model for activity times. However, raw data on activity times are often subject to rounding and to the Parkinson effect. We address those factors in our statistical tests by using a generalized version of the Parkinson distribution with random censoring of earliness, ultimately validating our model with field data from several sources. We also confirm that project activities exhibit stochastic dependence that can be modeled by linear association. <s> BIB002
A random variable X is lognormal if the probability density function is given as ( ) strated with examples that their methods are better than the normal approximation when the underlying activity distribution is skewed to the right and better than the classical PERT method only when the activity distribution is heavily right skewed. Trietsch, et al. BIB002 suggested the use of lognormal distribution for modeling activity times but by the Parkinson effect distribution. They further considered that project activities exhibit stochastic dependence that can be modeled by linear association. Some theoretical and empirical justifications were presented as a justification for the use of the model. For more on lognormal activity time see Perry and Greig BIB001 .