Probability distribution

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Probability distribution

A probability distribution (pronounced: prɒbəˈbɪlɪti dɪstrɪˈbjuːʃən) is a statistical function that describes all the possible values and likelihoods that a random variable can take within a given range. This range will be between the minimum and maximum statistically possible values, but where the possible value is likely to be plotted on the probability distribution depends on a number of factors. These factors include the distribution's mean (average), standard deviation, skewness, and kurtosis.

Etymology

The term "probability distribution" is derived from the mathematical study of probability and statistics. "Probability" (from the Latin probabilitas) refers to the measure of the likelihood that an event will occur, while "distribution" (from the Latin distributio) refers to the way something is spread out or arranged.

Types of Probability Distributions

There are several types of probability distributions, including but not limited to:

  • Normal distribution: Also known as Gaussian distribution, it is a type of continuous probability distribution for a real-valued random variable. The general form of its probability density function is symmetric, forming a bell curve.
  • Binomial distribution: This is a discrete probability distribution of the number of successes in a sequence of n independent experiments.
  • Poisson distribution: Named after French mathematician Siméon Denis Poisson, it is a discrete probability distribution that expresses the probability of a given number of events occurring in a fixed interval of time or space.
  • Exponential distribution: It describes the time between events in a Poisson point process, i.e., a process in which events occur continuously and independently at a constant average rate.

Related Terms

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