Assume that f is twice differentiable, i.e the Hessian matrix exists at each point in Df. Then f is convex if and only if Df is a convex set and its Hessian is positive semi-definite for all x∈Df. For a single-variable function this reduces to f″(x)≥0. Geometrically this means that f has nonnegative curvature everywhere.
This condition is particularly useful since it gives us an procedure for determining if the function under consideration is convex, apart from using the definition.