What is a non-random variable

Translation of "Random variable" in English

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The initial condition F is a B-valued one Random variable.
The Random variable is evenly distributed between -0.5 and +0.5.
The demand for each product is time dependent and as Random variable modeled.
Demand for each product is time-dependent and modeled by a random variable.
The Random variable dz represents a collection of random influences over the distance DT.
The random variable dz represents an accumulation of random influences over the interval dt.
See also: algebra of expectation values, Random variable
The result is a discrete one Random variable.
In information theory, entropy is a measure of the uncertainty with which one is exposed Random variable connected.
In information theory, entropy is a measure of the uncertainty associated with a random variable.
Note: Without loss of generality, we assume that the Random variable can take the first n positive integers.
Remark: Without losing generality we assume that the random variable can adopt the first n positive integers.
This is a non-uniformly distributed one Random variablewhose distribution we know in advance and which does not change.
This is a non-uniformly distributed random variable, whose distribution we know in advance and which does not change.
The change in the Random variable z over this interval of time is dz.
The function that assigns the average speed of molecules to a numerical value (temperature) is called continuous Random variable designated.
The function which assigns the average speed of molecules to a numerical value (the temperature) is called a continuous random variable.
See also: distributions, parameters, Venn diagrams, Random variable, Representative samples
Index See also: Venn diagram, parameters, distribution, random variable, representative samples
Hint: A simple trick to get a normally distributed Random variable To generate numerically is to take 16 numbers from a uniform distribution and divide the means by 4.
Hint: A common trick to numerically create a normally distributed random variable is to draw 16 numbers of a uniform symmetric distribution and divide the mean by 4.
Obviously, if we want to simulate such a random walk, we need one Random variable for the stagger directions "left" and "right", the probabilities of which can be adjusted dynamically.
If we want to simulate such a random walk, we need a random variable for the staggering directions "left" and "right", obviously, whose probabilities allow to be adapted dynamically.
Note: the terms Random variable and random number are often confused, but apart from the word "random" they have nothing in common.
Hint: The terms random variable and random number are often mixed up, although they have nothing in common except the word "random".
The method of claim 1, wherein the cumulative distribution function is a normal cumulative distribution function, where the logarithm of the equilibrium hydrogen pressure as Random variable is used and the standard deviation of the normal cumulative distribution function is used as an evaluation criterion.
A method as defined in claim 1 wherein the cumulative distribution function is a normal cumulative distribution function, the logarithm of the equilibrium hydrogen pressure is taken as a random variable, and the standard deviation from the normal cumulative distribution function is used as an evaluation criterion.
A Random variable is almost certainly constant if and only if its variance is zero.
Method according to Claim 6, characterized in that the expected value of the first is the first and second characteristic variable Random variable 〈T ON〉 and the average occupancy probability P ON (∞) can be determined.
Method in accordance with claim 6, characterized in that the expected value of the first random variable and the average occupancy probability P ON (∞) are determined as first and second characteristics.
The deviation of a Random variableThe accumulation of independent effects over an interval of time is proportional to the length of the interval, in this case DT.
The variance of a random variable which is the accumulation of independent effects over an interval of time is proportional to the length of the interval, in this case dt.
For the starting value x (0), a suitable estimated value x0 must be specified, which is the expected value of a Random variable for x (0) is taken.
A suitable estimate value x0, which is interpreted as the expected value of a random variable for x (0), must be indicated for the initial value x (0).
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