Probability Distributions
Explore every supported probability distribution. Each page includes interactive charts, formulas, quantile tools, and parameter controls.
A flexible distribution plotter for probabilities, proportions, and rates bounded between 0 and 1.
Discrete probability of k successes in n independent Bernoulli trials with probability p.
A heavy-tailed distribution where mean and variance are undefined. Educational for understanding pathological distributions.
Used to test if data fits a model (goodness of fit) or if variables are independent.
Models the time between independent events that happen at a constant average rate.
Used in ANOVA and regression analysis to compare variances between groups.
A flexible distribution for positive continuous data, often used to model waiting times and rainfall.
The number of failures before the first success in independent Bernoulli trials.
A distribution of a random variable whose logarithm is normally distributed. Common in finance and biology.
Models the number of failures before achieving a fixed number of successes. Common for overdispersed count data.
A bell-shaped, symmetric distribution for real‑valued variables. The mean sets the center and the standard deviation controls the spread.
A power-law distribution modeling wealth, city sizes, and the famous 80-20 rule.
Discrete probability of a given number of events occurring in a fixed interval.
Similar to the normal distribution but with heavier tails; used for estimating means of small samples.
A continuous distribution where all intervals of the same length are equally probable.
A versatile distribution for reliability engineering, modeling time-to-failure and survival analysis.