<Tr> <Th> </Th> <Td> maximum deviation </Td> <Td> midrange </Td> </Tr> <P> The associated functions are called p - norms: respectively 0 - "norm", 1 - norm, 2 - norm, and ∞ - norm . The function corresponding to the L space is not a norm, and is thus often referred to in quotes: 0 - "norm". </P> <P> In equations, for a given (finite) data set X, thought of as a vector x = (x 1,..., x n) (\ displaystyle \ mathbf (x) = (x_ (1), \ ldots, x_ (n))), the dispersion about a point c is the "distance" from x to the constant vector c = (c,..., c) (\ displaystyle \ mathbf (c) = (c, \ ldots, c)) in the p - norm (normalized by the number of points n): </P> <Dl> <Dd> f p (c) = ‖ x − c ‖ p: = (1 n ∑ i = 1 n x i − c p) 1 / p . (\ displaystyle f_ (p) (c) = \ left \ \ mathbf (x) - \ mathbf (c) \ right \ _ (p): = (\ bigg () (\ frac (1) (n)) \ sum _ (i = 1) ^ (n) \ left x_ (i) - c \ right ^ (p) (\ bigg)) ^ (1 / p).) </Dd> </Dl>

What is central tendency elaborate measures of central tendency