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Probability & distributions calculators
Explore event counts, conditional probabilities and simple distribution models.
Choose the right calculation
A distribution model is an assumption about the process, not a guarantee about outcomes. Independence, constant probability and fixed interval definitions matter. Exactly-k probabilities differ from cumulative probabilities.
Find a tool for your question
Independent Events Probability Calculator
Find the probability that two independent events both occur.
At Least One Event Calculator
Calculate the probability of at least one success in independent identical trials.
Binomial Probability Calculator
Find the probability of exactly k successes in n independent identical trials.
Poisson Probability Calculator
Find the probability of a specific event count under a Poisson model.
Binomial Mean Calculator
Find the expected number of successes across identical independent trials.
Binomial Standard Deviation Calculator
Find the standard deviation of the success count in a binomial model.
Expected Monetary Value Calculator
Combine two mutually exclusive outcomes using a chosen probability.
Bayes Theorem Calculator
Update a prior probability using likelihoods for evidence under two alternatives.
Uniform Distribution Probability Calculator
Find probability over an interval within a continuous uniform distribution.
Exponential Survival Probability Calculator
Find the probability of waiting longer than a chosen time in an exponential model.
Does exactly two successes mean two or more?
No. Exactly two counts only outcomes with two successes. Two or more is a cumulative probability covering several counts.
Useful next steps in other categories
Weighted Percentage Calculator
Combine two percentages using their actual group sizes.
Test Grade Percentage Calculator
Convert earned marks into a percentage of available marks.
More statistics topics
Descriptive statistics
Summarise location, dispersion and standardised differences.
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Explore standard errors, normal-model margins and planning sample sizes.
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Explore covariance, correlation and fitted straight-line relationships.
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