Continuous random variable

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Continuous random variable

A random value that can take any fractional value within specified ranges, as contrasted with a discrete variable.

Continuous Random Variable

A random variable that may take any value within a given range. That is, unlike a discrete variable, a continuous random variable is not necessarily an integer.
References in periodicals archive ?
In this context, this study aimed to estimate the critical levels for soil attributes through the criterion of reduced continuous probability distribution (NCRIz) in areas under banana cultivation and evaluate the fertility of low-yield areas in the Apodi Plateau.
1993); the average strand angle with a SD or a range (Barnes 2002); continuous probability distributions such as the von Mises distribution (Harris and Johnson 1982, Shaler 1991, Xu and Suchsland 1998) and normal distribution (Chen et al.
The beta distribution is a family of continuous probability distributions defined on the interval (0, 1) parameterized by two positive shape parameters, typically denoted by a and b.
The methodology proposed in this article utilizes an expert judgment model within a Bayesian framework for the more complex case of continuous probability distributions, The most general form of Bayes' Theorem applies to discrete probability distributions, and relates the conditional and prior probabilities of two events using the following equation,
Chapter 5 introduces basic concepts of probability and also lays a platform for discrete and continuous probability distributions covered in Chapter 6 and 7 respectively.
In over 100 exercises, supported by the accompanying CD-ROM, she describes probability concepts, discrete probability distributions, continuous probability distributions, mathematical expectation, limit theorems, transitions to statistics, estimating theory, hypothesis testing theory, order statistics and quantiles, permutation analysis, bootstrap analysis, multiple sample analysis, linear least squares analysis and contingency truth analysis.
His topics include descriptive statistics, continuous probability distributions, hypothesis testing, regression and correlation methods, and design and analysis techniques for epidemiologic studies.
Continuous Probability Distributions with Appealing Statistical Properties.
Among the topics are descriptive statistics: tabular and graphical displays, discrete and continuous probability distributions, sampling and sampling distributions, comparisons involving proportions and a test of independence, and multiple regression.
The author has organized the twenty chapters that make up the main body of his text in four parts devoted to an introduction to environmental risk analysis, discrete probability distributions, continuous probability distributions, and applications.

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