Calculate probabilities and parameters for various probability distributions
Calculate probabilities and parameters for the normal (Gaussian) distribution with customizable mean and standard deviation.
Compute probabilities for the beta distribution with shape parameters α and β, ideal for modeling proportions.
Calculate probabilities for the gamma distribution with shape and scale parameters, useful for modeling waiting times.
Compute probabilities for the exponential distribution, perfect for modeling time between events.
Calculate probabilities for the Poisson distribution, ideal for modeling rare event occurrences.
Compute probabilities for the chi-square distribution, commonly used in hypothesis testing.
Calculate probabilities for the F distribution, essential for ANOVA and variance comparisons.
Compute probabilities for the t distribution, used in small sample statistical inference.
Calculate probabilities for the log-normal distribution, useful for modeling multiplicative processes.
Compute probabilities for the Weibull distribution, commonly used in reliability analysis.
Calculate probabilities for the uniform distribution, used when all outcomes in an interval are equally likely.
Compute probabilities for the triangular distribution, useful for modeling with limited sample data.
Calculate probabilities for the Pareto distribution, ideal for modeling power-law phenomena.