2012Unpublished venueRequires access

Probability Distributions

Ralph Vince

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Abstract

This chapter presents a discourse on probability distributions. Whereas the arithmetic mean is the most common of the types of measures of location, or central tendency of a body of data, the central value or location of a distribution is often the first thing one wants to know about a group of data, and data's variability or “width” around that central value is the next important thing one needs to know in probability distributions. Distributions under study in the chapter are normal distribution, lognormal distribution, uniform distribution, Bernoulli Distribution, Binomial Distribution, Geometric Distribution, Hypergeometric Distribution, Poisson Distribution, Exponential Distribution Chi-Square Distribution, Student's Distribution, Multinomial Distribution and Stable Paretian Distribution.

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What this paper is about

This chapter presents a discourse on probability distributions. Whereas the arithmetic mean is the most common of the types of measures of location, or central tendency of a body of data, the central value or location of a distribution is often the first thing one wants to know about a group of data, and data's variability or “width” around that central value is the next important thing one needs to know in probability distributions. Distributions under study in the chapter are normal distribution, lognormal distribution, uniform distribution, Bernoulli Distribution, Binomial Distribution, Geometric Distribution, Hypergeometric Distribution, Poisson Distribution, Exponential Distribution Chi-Square Distribution, Student's Distribution, Multinomial Distribution and Stable Paretian Distribution.

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Available abstract

This chapter presents a discourse on probability distributions. Whereas the arithmetic mean is the most common of the types of measures of location, or central tendency of a body of data, the central value or location of a distribution is often the first thing one wants to know about a group of data, and data's variability or “width” around that central value is the next important thing one needs to know in probability distributions. Distributions under study in the chapter are normal distribution, lognormal distribution, uniform distribution, Bernoulli Distribution, Binomial Distribution, Geometric Distribution, Hypergeometric Distribution, Poisson Distribution, Exponential Distribution Chi-Square Distribution, Student's Distribution, Multinomial Distribution and Stable Paretian Distribution.

Key concepts: Multinomial distribution, Beta-binomial distribution, Compound probability distribution, Univariate distribution, Log-Cauchy distribution, Mathematics, Inverse-chi-squared distribution, Distribution fitting

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