There are many different distributions in statistics, but some of the most common include:
Bernoulli distribution: A discrete distribution that takes on only two values, usually 0 and 1. Binomial distribution: A discrete distribution that counts the number of successes in a series of independent trials. Poisson distribution: A discrete distribution that models the number of events that occur in a given time interval. Exponential distribution: A continuous distribution that models the time between events. Gamma distribution: A continuous distribution that models the waiting time until a certain number of events have occurred. Normal distribution: A continuous distribution that is often used to model real-world data. Chi-squared distribution: A continuous distribution that is used to test the goodness of fit of a model to data. F distribution: A continuous distribution that is used to compare the variances of two or more populations. Student's t-distribution: A continuous distribution that is used to estimate the mean of a population when the sample size is small. This is just a small sample of the many different distributions that are used in statistics. The specific distribution that is used will depend on the specific problem that is being solved.