Discrete random variable

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Related to Discrete probability distribution: binomial distribution

Discrete random variable

A random variable that can take only a certain specified set of individual possible values-for example, the positive integers 1, 2, 3, . . . For example, stock prices are discrete random variables, because they can only take on certain values, such as $10.00, $10.01 and $10.02 and not $10.005, since stocks have a minimum tick size of $0.01. By way of contrast, stock returns are continuous not discrete random variables, since a stock's return could be any number.
Copyright © 2012, Campbell R. Harvey. All Rights Reserved.

Discrete Random Variable

A variable that can take only one of several definite values. For example, one's FICO score is a discrete random variable because it can only be a positive integer between 300 and 850.
Farlex Financial Dictionary. © 2012 Farlex, Inc. All Rights Reserved
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Dealing with random combinatorial structures needs to estimate the deviation of two discrete probability distributions in terms of the maximal distance between their generating functions over [0, 1].
The Formulations of Discrete Probability Distributions of Similarity Scores and ROC Curve
However, existing literature that addresses differences between these diverse methods often uses models that employ discrete probability distributions to support or refute either method.
This effect is due to using a discrete probability distribution with a limited range of outcomes.
Mittal, "New nonadditive measures of entropy for discrete probability distributions," Journal of Mathematical Sciences, vol.
"Probability & Statistics: Modular Learning Exercises" cover: (1) Basic Statistics Concepts; (2) The Normal Model; (3) Discrete Probability Distributions; and (4) Correlation and Regression.
Consider two discrete probability distributions, p and q.
Their chapters cover descriptive statistics, probability, discrete probability distributions, continuous probability distributions, sampling and sampling distributions, interval estimation, hypothesis tests, comparisons involving means, comparisons involving proportions and a test of independence, simple linear regression, and multiple regression.

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