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Binomial Probability Calculator

Calculate P(X=k) with Step-by-Step Derivation

Number of trials (n)
Number of successes (k)
Probability of success (p)

Binomial Probability Formula

P(X = k) = C(n, k) × p^k × (1-p)^(n-k)
Where: C(n,k) = n! / (k! × (n-k)!)
E[X] = n × p, Var(X) = n × p × (1-p)

Binomial probability calculates the probability of exactly k successes in n independent Bernoulli trials.

p must be between 0 and 1, k must be between 0 and n.

What is Binomial Probability?

The binomial distribution models the number of successes in a fixed number of independent trials, each with two possible outcomes (success or failure) and constant probability of success.

Conditions

Fixed n, independent trials, two outcomes, constant p

Formula

P(X=k) = C(n,k) × p^k × (1-p)^(n-k)

Expected Value

E[X] = n × p, average number of successes

Variance

Var(X) = n × p × (1-p), spread of distribution

💡 Example: n=10, k=3, p=0.5. P(X=3) = C(10,3) × 0.5³ × 0.5⁷ = 120 × 0.125 × 0.0078125 = 0.1172.

Applications

Probability Statistics Quality Control Risk Analysis Survey Sampling

Frequently Asked Questions

What is binomial probability?
Binomial probability calculates the probability of exactly k successes in n independent trials, each with success probability p. P(X=k) = C(n,k) × p^k × (1-p)^(n-k).
What are the requirements for binomial distribution?
Fixed number of trials, independent trials, two possible outcomes (success/failure), constant probability of success for each trial.
What is expected value of binomial distribution?
E[X] = n × p. The expected number of successes is the number of trials times the probability of success.
What is variance of binomial distribution?
Var(X) = n × p × (1-p). Standard deviation = sqrt(n × p × (1-p)).

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