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Conditional variance

💡 Words with a Similar Meaning to "Conditional variance"

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WordDefinition
regular conditional probabilityIn probability theory, regular conditional probability is a concept that formalizes the notion of conditioning on the outcome of a random variable.
covariancenoun(statistics) A statistical measure defined as scriptstyle operatorname Cov(X,Y)= operatorname E((X-μ)(Y-ν)) given two real-valued random variables X and Y, with expected values scriptstyle E(X),=,μ and scriptstyle E(Y),=,ν.
conditional probabilitynounThe probability that an event will take place given the restrictive assumption that another event has taken place, or that a combination of other events has taken place. (Mathematically, the definition would be that the conditional probability of B given A is equal to the joint probability of A and B divided by the probability of A.)
marginal distributionnounThe projection of a joint probability distribution onto one of its component random variables.
probability distributionnoun(statistics) A distribution of all possible values of a random variable together with an indication of their probabilities.
random variateIn probability and statistics, a random variate or simply variate is a particular outcome or realization of a random variable; the random variates which are other outcomes of the same random variable might have different values (random numbers).
posterior predictive distributionIn Bayesian statistics, the posterior predictive distribution is the distribution of possible unobserved values conditional on the observed values.
random effects modelIn econometrics, a random effects model, also called a variance components model, is a statistical model where the model parameters are random variables.
conditional probability tableIn statistics, the conditional probability table is defined for a set of discrete and mutually dependent random variables to display conditional probabilities of a single variable with respect to the others (i.e., the probability of each possible value of one variable if we know the values taken on by the other variables).
conditional dependenceIn probability theory, conditional dependence is a relationship between two or more events that are dependent when a third event occurs.
probability mass functionnoun(mathematics) A function that gives the relative probability that a discrete random variable is exactly equal to some value.
distributionnounAn act of distributing or state of being distributed.
conditional mutual informationIn probability theory, particularly information theory, the conditional mutual information is, in its most basic form, the expected value of the mutual information of two random variables given the value of a third.
random variablenoun(statistics, loosely) A quantity whose value is random and to which a probability distribution is assigned, such as the possible outcome of a roll of a dice.
coefficient of variationIn probability theory and statistics, the coefficient of variation, also known as normalized root-mean-square deviation, percent RMS, and relative standard deviation, is a standardized measure of dispersion of a probability distribution or frequency distribution.
pairwise independenceIn probability theory, a pairwise independent collection of random variables is a set of random variables any two of which are independent.
conditional expectationIn probability theory, the conditional expectation, conditional expected value, or conditional mean of a random variable is its expected value evaluated with respect to the conditional probability distribution.
conditional entropynoun(information theory) The portion of a random variable's own Shannon entropy which is independent from another, given, random variable.
stochastic processnoun(mathematics, probability theory) A function that maps elements of an index set to elements of a collection of random variables; historically, a collection of random variables indexed by a set of numbers usually regarded as points in time.
stochastic volatilityIn statistics, stochastic volatility models are those in which the variance of a stochastic process is itself randomly distributed.

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