Examples of using Random variable in English and their translations into Slovak
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Colloquial
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Official
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Medicine
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Financial
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Ecclesiastic
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Official/political
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Computer
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Programming
I(X) is itself a random variable.
We defined our random variable, x, as the number of shots I make out of 6.
Stochastic" means being or having a random variable.
The random variable X has a binomial distribution with parameters n and p.
Information theory: Entropy is a measure of the uncertainty associated with a random variable.
TINV is calculated as TINV= p(t<X), where X is a random variable that follows the t-distribution.
Suppose the demand for a calendar is governed by the following discrete random variable.
TINV is calculated as TINV= p(t<X), where X is a random variable that follows the t-distribution.
They believe their demand for People is governed by the following discrete random variable.
For a random variable having probability density p(x), any point at which p(x) has a maximum is said to be a mode.
Suppose the demand for a calendar is governed by the following discrete random variable.
A discrete random variable is a random variable that takes on a finite or countably infinite number of values.
They believe their demand forPeople is governed by the following discrete random variable.
The distribution of a random variable X is discrete, if it can assume only a finite or countably infinite number of values.
Suppose that the demand for a Valentine's Daycard is governed by the following discrete random variable.
TDIST is calculated as TDIST= p(x<abs(X)), where X is a random variable that follows the t-distribution.
Suppose that the demand for a Valentine's Day card is governed by the following discrete random variable.
RT=P( Fgt;x), where F is a random variable that has an F distribution with deg_freedom1 and deg_freedom2 degrees of freedom.
If Tails= 1, TDIST is calculated as TDIST= P( Xgt;x),where X is a random variable that follows the t-distribution.
Elo's central assumption was that the chess performance of eachplayer in each game is a normally distributed random variable.
A random variable X follows the hypergeometric distribution with parameters N, m and n andf the probability is given by.
The inverse cumulative distribution function for a standard normal random variable(i.e. the value x such that N(x)= z);
The random variable X follows the Hypergeometric Distribution with parameters N, m and n, then the probability of getting exactly k successes is given by.
Denotes the inverse cumulative distribution function for a standard normal random variable(i.e. the value x such that= z).
FDIST is calculated as FDIST=P( Fgt;x), where F is a random variable that has an F distribution with deg_freedom1 and deg_freedom2 degrees of freedom.
A random mapping between an initial state and a final state,making the state of the system a random variable with a corresponding probability distribution.
Each item is considered to be a discrete random variable stochastically related to the mastery states and realized by observed values zN.
Let's suppose we want to simulate 400 trials, or iterations,for a normal random variable with a mean of 40,000 and a standard deviation of 10,000.
Let's suppose we want to simulate 400 trials, or iterations,for a normal random variable with a mean of 40,000 and a standard deviation of 10,000.