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Covariance vs Covariate - What's the difference?

covariance | covariate | Related terms |

Covariate is a related term of covariance.



In statistics terms the difference between covariance and covariate

is that covariance is a statistical measure defined as \scriptstyle\operatorname{Cov}(X, Y) = \operatorname{E}((X - \mu) (Y - \nu)) given two real-valued random variables X and Y, with expected values \scriptstyle E(X)\,=\,\mu and \scriptstyle E(Y)\,=\,\nu while covariate is a variable that is possibly predictive of the outcome under study.

covariance

Noun

(en noun)
  • (statistics) A statistical measure defined as \scriptstyle\operatorname{Cov}(X, Y) = \operatorname{E}((X - \mu) (Y - \nu)) given two real-valued random variables X'' and ''Y , with expected values \scriptstyle E(X)\,=\,\mu and \scriptstyle E(Y)\,=\,\nu.
  • (computing, programming) The conversion of data types from wider to narrower in certain situations.
  • See also

    * contravariance

    Derived terms

    * covariance matrix

    covariate

    Noun

    (en noun)
  • (statistics) A variable that is possibly predictive of the outcome under study.
  • *{{quote-journal, 2009, date=February 6, Christophe Fraser et al., The Bacterial Species Challenge: Making Sense of Genetic and Ecological Diversity, Science citation
  • , passage=On the basis of these analogies, any inference of a population structure driven by selective sweeps would require good longitudinal data from natural bacterial populations, as well as observations of episodic crashes in diversity causally associated with genetic changes and not associated with changes in ecological covariates . }}