Examples of using Random variable in English and their translations into Spanish
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If X{\displaystyle X} is a random variable, its cumulative distribution function F X( x)
method that produces the random variable is not clearly defined.
can be arbitrarily high for a random variable X{\displaystyle X}
It was noted that the krill predator functional relation model required an additional random variable(relating krill biomass to availability)
Often, one is interested in solely the spatial influence of a given random variable, say the direction of a spin,
The categorical distribution is the generalization of the Bernoulli distribution for a categorical random variable, i.e. for a discrete variable with more than two possible outcomes,
It is easy to see by symmetry that for a random variable X having this distribution,
is the distribution of a random variable X for which the Box-Cox transformation on X follows a truncated normal distribution.
That is, the receiver measures a signal that is equal to the sum of the signal encoding the desired information and a continuous random variable that represents the noise.
the content added to individual cups shows some variation, and is considered a random variable X. This variation is assumed to be normally distributed around the desired average of 250 g,
if r is a random variable that is one when hmin(A)
Nature assigns a random variable to each player which could take values of types for each player
The second view is the probabilistic view: the random variable F f( G){\displaystyle\textstyleF=f(G)} depends upon the random variable G g( H){\displaystyle\textstyleG=g(H)}, which depends upon H h( X){\displaystyle\textstyleH=h(X)}, which depends upon the random variable X{\displaystyle\textstyle X.
This is particularly common in probability theory when v is the cumulative distribution function of a real-valued random variable X, in which case∫-∞∞ f( x) d v( x)
X3,… is a random variable τ with the property that for each t,
of a random variable X{\displaystyle X},
if N is a random variable with a Poisson distribution,
He regarded the increment of particle positions in time τ{\displaystyle\tau} in a one dimensional(x) space(with the coordinates chosen so that the origin lies at the initial position of the particle) as a random variable( Δ{\displaystyle\Delta})
is a discrete probability distribution that describes the possible results of a random variable that can take on one of K possible categories,