Statistical Functions
Function | Description | Syntax |
---|---|---|
BernoulliDist | Returns a value of 1 or 0; the argument indicates how frequently the value of 1 is returned on a percentage basis. For example: BernoulliDist(0.7) implies a value of 1 is returned 70% of the time. | BernoulliDist(Probability) |
BetaDist | Returns the cumulative Beta probability density function between the minimum and maximum values that you supply. The BetaDist function is commonly used to study variation in a percentage across samples. | BetaDist(A,B,Min, Max) |
Between | Provides a uniformly-distributed number between the minimum and maximum values that you supply. For example, if you use Between(10,20), the value returned has an equal probability of being any real number from 10 to 20, both numbers inclusive. For example: 12.5 or 16.413. | Between(Min,Max) |
BetweenNorm | Provides a Normal random variable between a minimum and maximum value. For example, if you use BetweenNorm(10,20), the value returned is more likely to be 14, 15, or 16, and seldom 10 or 20. The BetweenNorm function is the same as the NormDist function except that the mean and standard deviation are calculated automatically according to the minimum and maximum values that you provide. Also, the value returned is always inside the specified range. | BetweenNorm(Min,Max) |
BinomDist | Models drawing or selecting items from a pool, where N is the number of items in the pool and Probability is the probability of each item being successfully drawn. | BinomDist(N,Probability) |
ErlangDist | Generates random values where N is the mean distribution and B is the variance. Both N and B must be greater than zero and N is an integer. (The Erlang distribution is a subset of the Gamma distribution.) | ErlangDist(N,B) |
ExponDist | Returns a pseudo-random value from the Exponential distribution. The value is always positive and is explained completely by specifying a single argument, the Mean. For example, if you specify ExponDist(15), the values, over time, tends to cluster around 15. Spikes of much larger values are always possible with the exponential distribution, so the Max argument is provided to truncate the distribution. If Max is supplied, no value larger than Max is returned. If, after trying 50 samples, no value is obtained less than Max, the value from the uniform distribution between 0 and Max is returned, and no warning is issued. This can happen with poorly chosen Max values, such as a value less than Mean. The function used to calculate the value is: Mean * -ln(1-x) where ln is the natural logarithm function and x is a pseudo-random value from the uniform distribution between 0 and 1. | ExponDist(Mean, Max) |
GammaDist | Generates random values with the following density: | GammaDist(A,B) |
LogNormDist | Is the logarithmic normal distribution. The first parameter is the mean and the second is the variance (deviation squared). | LogNormDist(Mean,Deviation) |
NormDist | Provides a Normal random variable indicated by its mean and its standard deviation. | NormDist(Mean,Deviation) |
NormSDist | Provides a standard normal random variable where the mean is 0 and the standard deviation is 1. This function does not take any arguments. The value is generated within the distribution curve. | NormSDist() |
PercentTrue | Returns true Num% of the time. For example, PercentTrue(95) becomes true 95% of the time | PercentTrue(Num) |
PercentFalse | Returns false Num% of the time. For example, PercentFalse(95) becomes true 95% of the time | PercentFalse(Num) |
PoissonDist | Is a limiting form of the Binomial distribution when, in the Binomial expression, N tends to infinity and Probability tends to zero at the same time. Exponential interarrivals are the same as Poisson arrivals. | PoissonDist(Mean) |
ProportionalDist | Generates a random proportional distribution. Let Sum = Num0 + Num1 + ... + Num(n); 0 <= n <= 11; Num0, Num1, ..., Num(n) >= 0. If Sum = 0, return -1, else return the integer value i, 0 <= i <= n, with the probability of Num(i)/Sum. | ProportionalDist(Num0,Num1,[...]) |
Random | Provides a random real number between 0 and 1, based on a uniform distribution. | Random() |
TriangleDist | Returns the value of a triangle-shaped distribution. The arguments Min and Max determine the smallest and largest values to return. Mode returns the most likely or peak value of the distribution. | TriangleDist(Min,Max,Mode) |
WeibullDist | Typically used for reliability analysis. It takes two parameters, A and B. Both must be greater than 0. Generates random values with the following density: ABx^{B-}^{1}exp(-Ax^{B}) | WeibullDist(A,B) |
WeibullStdDist | Is the Weibull distribution that takes two parameters. The first parameter is the shape and the second is the scale. It is the same distribution as WeibullDist(A, B) where A = 1 / (scale^{shape}) and B = shape. | WeibullStdDist(Shape,Scale) |