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In probability theory and statistics, the binomial distribution with parameters n and p is the discrete probability distribution of the number of successes in a sequence of n independent experiments, each asking a yes–no question, and each with its own Boolean-valued outcome: success (with probability p) or failure (with probability q = 1 − p).
Binomial Calculator computes individual and cumulative binomial probability. Fast, easy, accurate. An online statistical table. Sample problems and solutions.
In probability theory and statistics, the binomial distribution is the discrete probability distribution that gives only two possible results in an experiment, either Success or Failure.
Use the binomial distribution formula to find the probability, mean, and variance for a binomial distribution. Complete with worked examples.
The General Binomial Probability Formula: P(k out of n) = n!k!(n-k)! p k (1-p) (n-k) Mean value of X: μ = np; Variance of X: σ 2 = np(1-p) Standard Deviation of X: σ = √(np(1-p))
The binomial distribution evaluates the probability for an outcome to either succeed or fail. These are called mutually exclusive outcomes, which means you either have one or the other — but not both at the same time.
Binomial distribution is a fundamental probability distribution in statistics, used to model the number of successes in a fixed number of independent trials, where each trial has only two possible outcomes: success or failure.