Which of the following is NOT a type of probability distribution?

The concept of probability distributions is fundamental in statistics and probability theory, and each of the types listed except the chosen answer corresponds to well-defined distributions used to describe different types of statistical phenomena.

The binomial distribution is employed when dealing with a fixed number of independent trials, each having two possible outcomes, typically referred to as "success" and "failure." This distribution is widely used in scenarios such as quality control, genetics, and yes/no experiments.

The normal distribution, often called the Gaussian distribution, is one of the most important probability distributions in statistics. It describes data that cluster around a mean, showing that data near the mean are more frequent in occurrence than data far from the mean. The normal distribution is characterized by its bell-shaped curve, and it has applications in natural and social sciences.

The Poisson distribution is used to model the number of events occurring within a fixed interval of time or space. It is particularly useful for instances where events happen independently and the average rate (or intensity) of occurrence is known. Applications include modeling the number of phone calls received at a call center in a given hour or the occurrence of mutations in a given stretch of DNA.

In contrast, a linear distribution does not represent a recognized type of probability distribution in statistics.