Types of probability distributions

Probability mass function

In probability and statistics, a probability mass function is a function that gives the probability that a discrete random variable is exactly equal to some value. Sometimes it is also known as the discrete density function. The probability mass function is often the primary means of defining a discrete probability distribution, and such functions exist for either scalar or multivariate random variables whose domain is discrete. A probability mass function differs from a probability density function (PDF) in that the latter is associated with continuous rather than discrete random variables. A PDF must be integrated over an interval to yield a probability. The value of the random variable having the largest probability mass is called the mode. (Wikipedia).

Probability mass function
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Example of Probability Density Function

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Probability Distribution Functions

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Probability Density Function of the Normal Distribution

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From playlist Random Variables

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From playlist Probability Theory

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Related pages

Mode (statistics) | Discretization of continuous features | Statistics | Probability density function | Probability space | Cumulative distribution function | Multivariate random variable | Domain of a function | Joint probability distribution | Real number | Multinomial distribution | Probability distribution | Probability measure | Counting measure | Geometric distribution | Binomial distribution | Measure space | Probability theory | Pushforward measure | Categorical distribution | Bernoulli distribution | Image (mathematics)