(mathematical analysis) The inequality that states that the magnitude of the sum of two vectors is less than or equal to the sum of the magnitudes of the vectors, or any equivalent inequality in other spaces.

(statistics) The theorem that in any data sample with finite variance, the probability of any random variable X that lies k or more standard deviations away from the mean is no more than 1/k², i.e. assuming mean μ and standard deviation σ, the probability is:

(astronomy) A disturbance in the motion of a planet due to its position in its orbit relative to another planet.

(mathematics) An inequality that establishes that the Lp spaces are normed vector spaces.

(linear algebra) Cauchy-Schwarz inequality

(convex analysis) A particular inequality about convex functions, similar to Jensen's inequality. / (probability) An upper bound on the variance of any bounded probability distribution.

(mathematics) An inequality that relates the value of a convex function of an integral to the integral of the convex function.

Used other than figuratively or idiomatically: see marriage, inequality. / The state of same-sex couples being unable to legally marry.

The fact that the arithmetic mean of nonnegative numbers is not less than their geometric mean, and is more if some of the numbers are distinct.

(linear algebra, mathematical analysis) A theorem which states that the absolute value of the dot product between two vectors is less than or equal to the product of the magnitudes of the two vectors.