Linear Dependence Between Random Variables
The covariance is sometimes called a measure of "linear dependence" between two random variables. That does not mean the same thing as in the context of linear algebra. When the covariance is normalized, one obtains the correlation matrix. From it, one can obtain the Pearson coefficient, which gives us the goodness of the fit for the best possible linear function describing the relation between the variables. In this sense covariance is a linear gauge of dependence.
Read more about this topic: Linear Independence
Famous quotes containing the words dependence, random and/or variables:
“The invalid is a parasite on society. In a certain state it is indecent to go on living. To vegetate on in cowardly dependence on physicians and medicaments after the meaning of life, the right to life, has been lost ought to entail the profound contempt of society.”
—Friedrich Nietzsche (1844–1900)
“... the random talk of people who have no chance of immortality and thus can speak their minds out has a setting, often, of lights, streets, houses, human beings, beautiful or grotesque, which will weave itself into the moment for ever.”
—Virginia Woolf (1882–1941)
“The variables are surprisingly few.... One can whip or be whipped; one can eat excrement or quaff urine; mouth and private part can be meet in this or that commerce. After which there is the gray of morning and the sour knowledge that things have remained fairly generally the same since man first met goat and woman.”
—George Steiner (b. 1929)