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Represents the number of events in a fixed interval of time or space; events occur independently; often used for forecasting rare events

Distribution of a variable whose logarithm is normally distributed; skewed to the right; used to model stock prices and incomes

Similar to the normal distribution but with heavier tails; used in logistic regression and neural networks; characterized by location and scale parameters

Describes many types of economic, scientific, and natural phenomena; '80/20 rule'; heavy tails and sometimes called a power-law distribution

Simplest case of the binomial distribution; single trial with two possible outcomes; often used to model binary data

Number of successes in a series of draws from a finite population without replacement; used in sampling without replacement

Similar to the normal distribution but with heavier tails, resulting in a mean and variance that are undefined; often used in physics for resonance behavior

Number of trials until achieving a specified number of successes; generalization of the geometric distribution; models overdispersed count data

Continuous distribution on the interval [0, 1]; used to model random variables that are constrained to an interval; flexible shape depending on two shape parameters

Generalization of the chi-squared and exponential distributions; used for modeling wait times and lifetimes; two parameters: shape and scale

Models the magnitude of a vector that is composed of two independent and identically distributed normal random variables; used in signal processing

Another name for the exponential distribution; used to describe the time between events in a Poisson point process

Ratio of two scaled chi-squared variables; used in analysis of variance (ANOVA); characterized by degrees of freedom for the numerator and denominator

All outcomes in a finite sample space are equally likely; characterized by number of outcomes; used in fairness considerations, such as lotteries or games of chance

Two-dimensional extension of the normal distribution; characterized by means, variances, and correlation coefficient; used in multivariate analysis

Multivariate generalization of the beta distribution; used in Bayesian statistics, machine learning, and document classification

Similar to normal distribution but with heavier tails; used for small sample sizes; characterized by degrees of freedom

Number of trials until first success; each trial is independent with the same probability of success; memoryless property

Symmetrical, bell-shaped distribution; characterized by its mean and standard deviation; used in many natural and social phenomena

Flexible life data analysis model for fitting the breaking strength of materials, life times of objects; two parameters shape (k) and scale (λ)

Generalization of the binomial distribution; outcomes that can fall into more than two categories; used in marketing research and election predictions

All outcomes are equally likely; continuous or discrete; defined by minimum and maximum values

Discrete distribution showing number of successes in a fixed number of independent trials; fixed probability of success; uses in quality control and survey sampling

Continuous distribution for modeling time until the next event; memoryless property; often used in reliability engineering and queuing theory