Examples of using Random variable in English and their translations into Italian
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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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Ecclesiastic
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Computer
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Programming
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Official/political
Measure of the information of a discrete random variable.
Let L(for traffic light) be a discrete random variable taking one value from{Red, Yellow, Green.
How can you simulate values of a normal random variable?
For a normal distributed random variable X with given mean μ
Probability function(of a discrete random variable);
Entropy===The entropy, formula_6, of a discrete random variable formula_7 is a measure of
Measure of the information: entropy of a discrete random variable.
The entropy HX of a discrete random variable X is a measure of the amount of uncertainty
Conditional distribution of probability of a random variable.
For a b(k;n;p) distributed random variable X with fixed n
Probability density(of a continuous random variable); expected value;
as the length of a stream of independent and identically-distributed random variable i.i.d.
If an is the probability mass function of a discrete random variable, then its ordinary generating function is
It is the axial symmetry of the density function of a random variable.
the information in a random variable, and mutual information, the amount of information in common between two random variables. .
Measurement result as a range of values; the measurement as a random variable.
message is an independent identically distributed random variable, whereas the properties of ergodicity and stationarity impose less restrictive constraints.
and X a T-valued integrable random variable.
If it can be shown that the random variable can take on a value less than the expected value,
skewness is a measure of the asymmetry of the probability distribution of a real-valued random variable about its mean.
a measure of information in a single random variable, and mutual information, a measure of information in common between two random variables. .
entropy is that:: formula_37===Mutual information(transinformation)===Mutual information measures the amount of information that can be obtained about one random variable by observing another.
Definition==Suppose that: formula_1i.e.,"N" is a random variable whose distribution is a Poisson distribution with expected value λ,
quantifies the amount of information needed to describe the outcome of a random variable Y{\displaystyle Y} given that the value of another random variable X{\displaystyle X} is known.
Loosely speaking, it states that if a random variable X is obtained by summing a large
The usefulness of these depends on what is already known about the random variable; for example a random variable may be defined in terms of its probability density function
The probability of any random variable Y can be written as probability
deriving algebraic expressions for the theoretical variance of a random variable, in contrast to questions of estimating the variance of a population
In probability, and statistics, a multivariate random variable or random vector is a list of mathematical