Eksempler på bruk av Random variable på Engelsk og deres oversettelse til Norsk
{-}
-
Colloquial
-
Ecclesiastic
-
Ecclesiastic
-
Computer
The sample mean is a random variable, not a constant,
The meaning of the probabilities assigned to the potential values of a random variable is not part of probability theory itself
NORMDIST returns the cumulative probability that the observed value of a Normal random variable with mean mu
each individual point must necessarily have probability zero for an absolutely continuous random variable.
it is commonly more convenient to map the sample space to a random variable which takes values which are real numbers.
A new random variable Y can be defined by applying a real Borel measurable function g: R→ R{\displaystyle g\colon\mathbb{R}\rightarrow\mathbb{R}} to the outcomes of a real-valued random variable X{\displaystyle X.
In measure-theoretic terms, we use the random variable X{\displaystyle X}
If the random variable is itself real-valued,
For example, for a categorical random variable X that can take on the nominal values"red","blue" or"green",
fully characterise the distribution of the random variable X{\displaystyle X.
In the measure-theoretic, axiomatic approach to probability, if a random variable X{\displaystyle X} on Ω{\displaystyle\Omega} and a Borel measurable function g: R→ R{\displaystyle g\colon\mathbb{R}\rightarrow\mathbb{R}}, then Y g( X){\displaystyle Y=g(X)} is also a random variable on Ω{\displaystyle\Omega},
Not all continuous random variables are absolutely continuous,
This article is about the measure of linear relation between random variables.
The chi-squared distribution, which is the sum of the squares of n independent Gaussian random variables.
Random Variables, 518.
Random variables and probability distribution.
for example: random variables, expectation, variance and standard deviation.
Continuous random variables.
The central objects of probability theory are random variables, stochastic processes, and events.
Lecture 8: Continuous random variables, expectation and variance.