Main Page | See live article | Alphabetical index A multivariate random variable or random vector is a vector X=(X1,...,Xn) whose components are scalar-valued random variables on the same probability space (Ω, P). Every such random vector gives rise to a probability measure on Rn with the Borel algebra as underlying sigma-algebra. This measure is also known as the joint distribution of the random vector. The distributions of each of the component random variables Xi are called marginal distributions. Table of contents 1 Conditional expectation 2 Independence 3 Covariance 4 Examples Conditional expectation Independence Covariance Examples Multivariate Gaussian distribution This article is from Wikipedia. All text is available under the terms of the GNU Free Documentation License.