Examples for

Probability Distributions
Probability distributions are functions that describe the likelihood of different outcomes of random phenomena in terms of how probable they are to occur. Wolfram|Alpha's exhaustive computational knowledge of both discrete probability mass functions and continuous probability distribution functions allows you to visualize relative probabilities and compute moments, expected values, standard deviations and all manner of observable properties of a wide range of distributions.

Continuous Distributions

Analyze properties, find moments and determine the likelihood of outcomes of continuous distributions.

Compute properties of a continuous distribution:

Specify parameters for a distribution:

Compute a particular property:

Compute a moment of a distribution:

Compute a central moment:

Compute a cumulant:

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Discrete Distributions

Analyze properties, find moments and determine the likelihood of outcomes of discrete distributions.

Compute properties of a discrete distribution:

Specify parameters for a distribution:

Compute a particular property:

Compute a moment of a distribution:

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