Examples of using A random variable in English and their translations into Greek
{-}
-
Colloquial
-
Official
-
Medicine
-
Ecclesiastic
-
Financial
-
Official/political
-
Computer
variance is the expectation of the squared deviation of a random variable from its mean, and it informally measures how far a set of(random)
The variance of a random variable X{\ displaystyle X} is the expected value of the squared deviation from the mean of X{\ displaystyle X}, μ= E{\ displaystyle\ mu=\ operatorname{ E}}: Var( X)= E.{\ displaystyle\ operatorname{ Var}( X)=\ operatorname{ E}\ left.}
By standardizing, we get a random variable.
Let X be a random variable with mean value μ.
Data are the observed values of a random variable.
Thus the sample mean is a random variable, not a constant, and consequently has its own distribution.
we are now assuming that each observation xi comes from a random variable that has its own distribution function fi.
Distribution of the sample varianceBeing a function of random variables, the sample variance is itself a random variable, and it is natural to study its distribution.
the information in a random variable, and mutual information, the amount of information in common between two random variables.
A random variable can take on a set of possible different values(similarly to other mathematical variables), each with an associated probability, in contrast to other mathematical variables. .
The special case of information entropy for a random variable with two outcomes is the binary entropy function,
if it were to converge to a random variable Y then we wouldn't be able to conclude that(Xn,
Because entropy can be conditioned on a random variable or on that random variable being a certain value,
β is a survival parameter in the sense that if a random variable X is the duration of time that a given biological
β is a survival parameter in the sense that if a random variable X is the duration of time that a given biological
β is a survival parameter in the sense that if a random variable X is the duration of time that a given biological
is considered a random variable X. This variation is assumed to be normally distributed around the desired average of 250 g, with a standard deviation, σ.
right tail event is a random variable, this makes the p-value a function of x{\displaystyle x} and a random variable in itself defined uniformly over[ 0, 1]{\displaystyle[0,1]} interval,
If X is a random variable representing the observed data
The special case of information entropy for a random variable with two outcomes is the binary entropy function, usually taken to the logarithmic base 2, thus having the shannon(Sh) as unit: :formula_21===Joint entropy===The joint entropy of two discrete random variables formula_7 and formula_23 is merely the entropy of their pairing: formula_24.