second derivative test

(1.7 hours to learn)


In an optimization problem, a critical point (where the partial derivatives are zero) may be a local minimum or maximum, or a saddle point. The second derivative test is a way of testing optimality: a point is a (local) minimum if the Hessian matrix is positive definite.


This concept has the prerequisites:

Core resources (read/watch one of the following)


Supplemental resources (the following are optional, but you may find them useful)


MIT Open Courseware: Multivariable Caclulus (2010)
Video lectures for MIT's introductory multivariable calculus class.
Author: Denis Auroux


See also

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