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Geometric Distribution Calculator

Calculate geometric distribution probability, mean, variance, and standard deviation for Bernoulli trials.

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What Is the Geometric Distribution?

The geometric distribution models the number of independent Bernoulli trials needed until the first success, or equivalently the number of failures before the first success. Classic examples include rolling a die until you get a six, flipping a coin until heads, or testing products until the first defect is found. For related discrete models, see the Binomial Probability Distribution Calculator or Negative Binomial Distribution Calculator.

Key Formulas

With $x$ failures before the first success and success probability $p$:

$$P(X = x) = (1-p)^x \cdot p$$

$$\mu = \frac{1-p}{p}, \quad \sigma^2 = \frac{1-p}{p^2}, \quad \sigma = \sqrt{\frac{1-p}{p^2}}$$

Example: Rolling a Die

Rolling a fair six-sided die until the first six has $p = 1/6$. The probability of exactly one failure before the first success ($x = 1$) is $P(X = 1) = (5/6) \times (1/6) \approx 0.1389$, or about 13.89%. The mean number of failures is $(1-p)/p = 5$.

Frequently Asked Questions

What does x represent?

$x$ is the number of failures before the first success. If you succeed on the first try, $x = 0$. If you fail once then succeed, $x = 1$.

What range can p take?

$p$ must be between 0 and 1 (exclusive of 0). It is the probability of success on each independent trial.

How is this different from the binomial distribution?

Binomial counts successes in a fixed number of trials. Geometric counts how many trials are needed until the first success.

Is the geometric distribution memoryless?

Yes. The number of additional failures needed after any number of past failures has the same distribution as from the start.

What is the expected number of trials until success?

The expected total trials is $1/p$. The expected failures before success is $(1-p)/p$, which is what this calculator reports as the mean.

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