A metric satisfies . A norm satisfies the corresponding inequality .
In a metric space, applying the triangle inequality in both directions gives . In a normed vector space, its corresponding form is . In particular, distance to a fixed point is a Lipschitz continuous real function.
For four points in a metric space,
Both steps follow from the triangle inequality. The first also holds with an absolute value around the difference, by the reverse triangle inequality. This transports a difference of distances measured from one point into a sum measured from another.
For an integrable function with values in a finite-dimensional normed vector space,
For the Euclidean norm, pair the integral with a unit vector in its direction and apply the Cauchy-Schwarz inequality pointwise.
For nonzero complex numbers , equality holds exactly when is a positive real number, equivalently when the two numbers have the same complex argument modulo .
For every integrable real or complex function,

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The triangle inequality is a fundamental concept in geometry and mathematics that states the following for any triangle with sides of lengths \( a \), \( b \), and \( c \): 1. \( a + b > c \) 2. \( a + c > b \) 3. \( b + c > a \) In essence, the triangle inequality asserts that the sum of the lengths of any two sides of a triangle must be greater than the length of the remaining side.