
LineoNormal Distribution
< Back to Probability Distributions List The Lineonormal distribution is a member of the modified normal distributions constructed by Romanowski [1]. He states “The lineonormal distributions seem to be strikingly well confirmed by types of observations and measurements”. M. Romanowski It is a special case of the modified normal cumulative distribution function (CDF) [2] with […]

Ghosh distribution
< Back to Probability Distributions List Haight [1] defines the Ghosh distribution as: where [k] is the largest integer ≤ k. The formula provides a counterexample to the theorem on similar regions in hypothesis testing (also called “regions similar to the sample space with respect to composite parameters”). Ghosh’s work revealed that all similar regions […]

Cumulative Distribution Function
< Probability distributions The cumulative distribution function (CDF) of a random variable is one way to describe the distribution of random variables. It is an extension of a cumulative frequency table, which measures discrete counts. However, one advantage of the CDF is that it can be defined for every type of random variable, such as discrete, continuous, or mixed. […]

Skewed Distribution
< Probability distributions A skewed distribution is a type of distribution in which one tail is longer than the other. These distributions are sometimes called asymmetric or asymmetrical distributions as they don’t show any kind of symmetry. Symmetry means that one half of the distribution is a mirror image of the other half. For example, […]

Survival Distribution
< List of probability distributions A survival distribution is the probability distribution of a survival function; a function which tells us how long before a process terminates, fails, or comes to an expected end. In other words, it’s a tool that can help us predict how long something will last. Survival distributions are used in […]

Compound distribution
< Probability distributions A compound probability distribution has random variables drawn from a “compound” parametric distribution, where one or more of the distributions parameters (i.e. the mean) are taken from other probability distributions. In other words, it is a probability distribution that is based on two or more other probability distributions. Compound probability distributions are […]

Rayleigh Distribution
< Probability distributions The Rayleigh distribution is a continuous probability distribution named after English Lord Rayleigh. It is a special case of the Weibull distribution with a scale parameter of 2. When a Rayleigh is set with a shape parameter (σ) of 1, it is equal to a chi square distribution with 2 degrees of […]

Population Definition in Statistics
< Statistics and Probability Definitions In statistics, a population is defined as a whole group of people or objects from which samples can be taken. A population is the opposite of a sample, which is a fraction or percentage of a group. For example, if you were interested in surveying dog owners to find out […]

GompertzRayleigh distribution
< List of probability distributions The GompertzRayleigh distribution is an extension of the Rayleigh distribution that allows for better modeling of highlyskewed (offcenter) datasets compared to compound distributions [1]. A similarly named but unrelated distribution is a generalized GompertzRayleigh distribution, proposed by Bradley [2] as a potential survival distribution for modeling risk. Many other generalized […]

Helmert’s Distribution
< Back to Probability Distribution List Helmert’s distribution is another name for the chisquare distribution. It is named after F.R. Helmert, who proved the general reproductive property of chisquare distributions [1]. About Helmert’s Distribution Helmert’s most noted contribution was establishing that if a set of independent, normally distributed random variables X1, X2, …, Xn, then […]