The Common Discrete Probability Functions

This is a companion Web site to
P-values for the Popular Distributions

This site is a part of the JavaScript E-labs learning objects for decision making. Other JavaScript in this series are categorized under different areas of applications in the MENU section on this page.

Professor Hossein Arsham   

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The following JavaScript compute the probability mass function (p) and cumulative distribution function (F) for the the widely used discrete random variable.

Discrete Random Variables: A discrete random variable is used to model a random outcome with a finite or countable number of possible outcomes. That is, a discrete random variable is one that may take on only a countable number of distinct values. If a random variable can take only a finite number of distinct values, then it must be discrete. Examples are the number of patients in a doctor's surgery, the number of defective light bulbs in a box of ten.

Probability Mass Function: The probability mass function of a discrete random variable is a list of probabilities associated with each of its possible values. It is also sometimes called the probability function or the probability mass function, i.e., p = P (X = x).

Cumulative Distribution Function: The cumulative distribution function of a random variable is a function giving the probability that the random variable X is less than or equal to x, for every value x, i.e. F = P(X £ x)

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1. Binomial
2. Negative-Binomial
3. Geometric
4. Poisson
5. Hypergeometric

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Binomial Probability

Enter the parameters (n) and (p), and (k), then click the Compute buttons to get P = P(X = k) and F = P(X £ k).

n	p	k
								P =		F =

For Technical Details, Back to:
Binomial Probability

Negative-Binomial Probability

Enter the parameters (r) and (p), and (k), then click the Compute buttons to get P = P(X = k) and F = P(X £ k).

r	p	k
								P =		F =

For Technical Details, Back to:
Negative-Binomial Probability

Geometric Probability

Enter the parameters (p), and (k), then click the Compute buttons to get P = P(X = k) and F = P(X £ k).

p	k
							P =			F =

For Technical Details, Back to:
Geometric Probability

Poisson Probability

Enter the parameters (l) and (k), then click the Compute buttons to get P = P(X = k) and F = P(X £ k).

l	k
							P =	F =

For Technical Details, Back to:
Poisson Probability

Hypergeometric Probability

Enter the parameters (n) and (p), and (k), then click the Compute buttons to get P = P(X = k) and F = P(X £ k).

M	N	n	k
	P =		F =

For Technical Details, Back to:
Hypergeometric Probability

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Back to:
Statistical Thinking for Decision Making

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Kindly email your comments to:
Professor Hossein Arsham

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Kindly e-mail me your comments, suggestions, and concerns. Thank you.

Professor Hossein Arsham   

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