Logistic distribution

Format: Logistic(a, b)

The Logistic distribution looks similar to the Normal distribution but has a kurtosis of 4.2 compared to the Normal kurtosis of 3. Examples of the Logistic distribution are given below:



The Logistic distribution is popular in demographic and economic modeling because it is similar to the Normal distribution but somewhat more peaked. It does not appear often in risk analysis modeling.


The cumulative function has also been used as a model for a 'growth curve'. Sometimes called the Sech-Squared distribution because its distribution function can be written in a form that includes a sech2. Its mathematical derivation is the limiting distribution as n approaches infinity of the standardised mid-range (average of the highest and lowest values) of a random sample of size n from an exponential-type distribution.

ModelRisk functions added to Microsoft Excel for the Logistic distribution

VoseLogistic generates random values from this distribution for Monte Carlo simulation, or calculates a percentile if used with a U parameter.

VoseLogisticObject constructs a distribution object for this distribution.

VoseLogisticProb returns the probability density or cumulative distribution function for this distribution.

VoseLogisticProb10 returns the log10 of the probability density or cumulative distribution function.

VoseLogisticFit generates values from this distribution fitted to data, or calculates a percentile from the fitted distribution.

VoseLogisticFitObject constructs a distribution object of this distribution fitted to data.

VoseLogisticFitP returns the parameters of this distribution fitted to data.

Logistic distribution equations



Monte Carlo simulation in Excel. Learn more


Adding risk and uncertainty to your project schedule. Learn more



For Microsoft Excel

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