# Second derivative test

﻿
Second derivative test

In calculus, a branch of mathematics, the second derivative test is a criterion often useful for determining whether a given stationary point of a function is a local maximum or a local minimum.

The test states: If the function $f$ is twice differentiable in a neighborhood of a stationary point $x$, meaning that $f^\left\{prime\right\}\left(x\right) = 0$, then:

* If $f^\left\{primeprime\right\}\left(x\right) < 0$ then $f$ has a local maximum at $x$.
* If $f^\left\{primeprime\right\}\left(x\right) > 0$ then $f$ has a local minimum at $x$.
* If $f^\left\{primeprime\right\}\left(x\right) = 0$, the second derivative test says nothing about the point $x$.

In the last case, the function may have a local maximum or minimum there, but the function is sufficiently "flat" that this is undetected by the second derivative. Such an example is $f\left(x\right) = x ^4$.

Multivariable case

For a function of more than one variable, the second derivative test generalizes to a test based on the eigenvalues of the function's Hessian matrix at the stationary point. In particular, assuming that all second order partial derivatives of "f" are continuous on a neighbourhood of a stationary point "x", then if the eigenvalues of the Hessian at "x" are all positive, then x is a local minimum. If the eigenvalues are all negative, then "x" is a local maximum, and if some are positive and some negative, then the point is a saddle point. If the Hessian matrix is singular, then the second derivative test is inconclusive.

Proof of Second Derivative Test

Suppose we have $f"\left(x\right) > 0$ (the proof for $f"\left(x\right) < 0$ is analogous). Then

:$0 < f"\left(x\right) = lim_\left\{h o 0\right\} frac\left\{f\text{'}\left(x + h\right) - f\text{'}\left(x\right)\right\}\left\{h\right\} = lim_\left\{h o 0\right\} frac\left\{f\text{'}\left(x + h\right) - 0\right\}\left\{h\right\} = lim_\left\{h o 0\right\} frac\left\{f\text{'}\left(x+h\right)\right\}\left\{h\right\}$

Thus, for "h" sufficiently small we get

:$frac\left\{f\text{'}\left(x+h\right)\right\}\left\{h\right\} > 0$which means that:$f\text{'}\left(x+h\right) < 0$ if "h" < 0, and:$f\text{'}\left(x+h\right) > 0$ if "h" > 0.

Now, by the first derivative test we know that $f$ has a local minimum at $x$.

Concavity test

The second derivative test may also be used to determine the concavity of a function as well as a function's points of inflection. First, all points at which $f\text{'}\left(x\right) = 0$ are found. In each of the intervals created, $f"\left(x\right)$ is then evaluated at a single point. For the intervals where the evaluated value of $f"\left(x\right) < 0$ the function $f\left(x\right)$ is concave down, and for all intervals between critical points where the evaluated value of $f"\left(x\right) > 0$ the function $f\left(x\right)$ is concave up. The points that separate intervals of opposing concavity are points of inflection.

ee also

* Fermat's theorem
* First derivative test
* Higher order derivative test
* Differentiability
* Extreme value
* Inflection point
* Convex function
* Concave function

References

* [http://mathworld.wolfram.com/SecondDerivativeTest.html Second Derivative Test from Mathworld]
* [http://www.math.hmc.edu/calculus/tutorials/secondderiv/ Concavity and the Second Derivative Test]
* [http://mathdl.maa.org/convergence/1/?pa=content&sa=viewDocument&nodeId=606&bodyId=948 Thomas Simpson's use of Second Derivative Test to Find Maxima and Minima] at [http://mathdl.maa.org/convergence/1/ Convergence]

Wikimedia Foundation. 2010.