Covariance is a statistical measure of how two random variables change together, computed as the expected value of the product of their deviations from their own means. A positive covariance indicates the variables tend to increase together, a negative covariance indicates one tends to increase as the other decreases, and a covariance near zero suggests little linear relationship. Because its size depends on the scale of the variables involved, covariance is often normalized into the dimensionless correlation coefficient. It underlies the variance-covariance matrix used throughout statistics, finance and machine learning to describe multivariate relationships. This description is adapted from Wikipedia contributors under CC BY-SA 4.0; changes were made. https://creativecommons.org/licenses/by-sa/4.0/
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Source Covariance (Wikipedia)
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Entity-backed identity for the object-kind enum value this mathematical object already carries, resolved to a mathematics concept by an explicit value-to-entity map (phase 3 bucket conversion, docs\design_entity_backed_browse_buckets_20260928.md). The object-kind fact itself stays on the object unchanged.
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1. Covariance (Wikipedia)
In Branch: Probability and Statistics, Lead sentenceQuote, In Branch: Probability and Statistics, Lead sentence
In probability theory and statistics, covariance is a measure of the joint variability of two random variables.
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