Forget about tables! This page allows you to work out accurate values of statistical functions associated to the most common probability distributions: Binomial Distribution, Geometric Distribution, Negative Binomial Distribution, Poisson Distribution, Hypergeometric Distribution, Normal Distribution, ChiSquare Distribution, Studentt Distribution, and FisherSnedecor F Distribution. For each one you can calculate Probability Density Function (PDF) or Probability Mass Function (PMF), Cumulative Distribution Function (CDF) and Complementary Cumulative Distribution Function (CCDF), Inverse Cumulative Distribution Function (CDF^{ 1}) and Inverse Complementary Cumulative Distribution Function (CCDF^{ 1}). Inverse functions return the value y such that P(X ≤ y) = x in the case of CDF^{ 1}, and P(X > y) = x in the case of CCDF^{ 1}. If the distribution is discrete, the returned integer value y fulfills the relation P(X ≤ y  1) < x ≤ P(X ≤ y) in the case of CDF^{ 1}, and P(X > y) ≤ x < P(X > y  1) in the case of CCDF^{ 1}. Expected value or mean, variance, skewness and kurtosis are also calculated. Some final notes to avoid confusion: the Geometric Distribution considered here corresponds to the distribution of the number of failures before the first success (and not to the distribution of the number of trials needed to get a success); similarly, the Negative Binomial Distribution corresponds to the distribution of the number of failures before getting a certain number of successes (and not to the distribution of the number of trials needed to get a certain number of successes).
