# Category: Statistical Distributions

## Weibull Distribution

Weibull Statistical Distribution   General Characteristics If a quantity X, is a ‘time-to-failure’, the Weibull distribution gives a distribution for which the failure rate is proportional to a power of time.   Specific Characteristics Key Measures: Shape, Scale   Range

## Negative Exponential Distribution

Negative Exponential Statistical Distribution   General Characteristics The Negative Exponential distribution has an inverted curve from the y-axis to the x-axis. Unlike Gamma distribution which involves two parameters, the Negative Exponential distribution involves only one parameter, and is thus easier

## Log Normal Distribution

Log Normal Statistical Distribution   General Characteristics Log Normal distribution is also referred to as Gibrat distribution, Galton’s distribution, McAlister distribution or Cobb-Douglas distribution. A positive variable X is Log-Normally distributed if its Logarithm is normally distributed.     Specific

## Truncated Normal Distribution

Truncated Normal Statistical Distribution   General Characteristics Truncated Normal Distribution is derived from a normally distributed random variable, by bounding the random variable from either below, above or both. Truncations can be either; one-sided of lower tail truncation, one-sided of

## Erlang Distribution

Erlang Statistical Distribution   General Characteristics The Erlang distribution is, like its ‘parent’ distribution, a two-parameter family of continuous probability distributions. It is a special case of Gamma distribution.     Specific Characteristics Key Measures: Mean, k   Range of

## Gamma Distribution

Gamma Statistical Distribution   General Characteristics The Gamma distribution is a two-parameter family of continuous probability distributions. Some statistical distributions are special cases of Gamma distribution including; Erlang distribution, Exponential distribution and Chi-Squared distribution.     Specific Characteristics Key Measures: