# Probability Density

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## probability density

[‚präb·ə′bil·əd·ē ‚den·səd·ē]
(quantum mechanics)
The square of the absolute value of the Schrödinger wave function for a particle at a given point; gives the probability per unit volume of finding the particle at that point.

## Probability Density

The probability density of a random variable X is a function p(x) such that for any a and b the inequality a < X < b has probability equal to

For example, if X has a normal distribution,

If p(x) is continuous, the probability of the inequality x < X < x + dx is approximately equal to p(x) dx for sufficiently small dx. The probability density always satisfies the conditions

The probability density p(x1,…, xs) for several random variables X1, X2,…, Xs is defined in a similar manner and is called the joint probability density. Thus, for any ai and bi, the probability that the inequalities a1 < X1 < b1,…, as < Xs < bs are simultaneously satisfied is equal to

If the random variables X1, X2,…, Xs have joint probability density, they will be independent if, and only if, their joint probability density is the product of the probability densities of each of them.

References in periodicals archive ?
The probability density function of the MLM has the shape parameter k = 1.
Exponential probability density model (EPDM) for mean velocity profile of turbulent shear flow
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Estimation of wind energy potential using different probability density functions.
Now predict the range of the the crosstalk of transmission lines in frequency domain by QMC method, and obtain the probability density distribution of the crosstalk of transmission lines under specific frequency at the same time.
Through dividing the statistical number of each energy state with the total times of the experiment, the accumulated probability density of solar energy state of the HybE-BS can be obtained.
Probability density generated and determined by formula (1) distribution density of the input voltage value [V.
Rice [6] described the probability density function of peak values for a narrowband process follows a Rayleigh distribution.
As the probability density functions of considered distributions depend on the particular parameter values, construction of the classifiers should be started from the estimation of these parameters for each category of pixels.
The radiation models have been coupled with two combustion models: the transported probability density function method and well-mixed model for turbulent reactive flows and soot, therefore capturing turbulence-chemistry-soot-radiation interactions.
To solve related problems, we need to have a thorough understanding on the structure of the underlying probability density.

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