SECOND DERIVATIVE TEST
In calculus, a branch of mathematics, the 'second derivative test' determines whether a given stationary point of a function is a maximum or a minimum.
The test states: If the function is twice differentiable in a neighborhood of a stationary point , then:
★ If then has a maximum at .
★ If then has a minimum at .
★ If , the second derivative test says nothing about the point .
Main articles: Second partial derivative test
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.
The second derivative test may also be used to determine the concavity of a function as well as a function's points of inflection.
Firstly, all points at which are found. In each of the intervals created, is then evaluated at a single point. For the intervals where the evaluated value of the function is concave down, and for all intervals between critical points where the evaluated value of the function is concave up. The points that separate intervals of opposing concavity are points of inflection.
★ Fermat's theorem
★ First derivative test
★ Higher order derivative test
★ Differentiability
★ Extreme value
★ Inflection point
★ Convex function
★ Concave function
★ Second Derivative Test from 'Mathworld'
★ Concavity and the Second Derivative Test
★ Thomas Simpson's use of Second Derivative Test to Find Maxima and Minima at Convergence
The test states: If the function is twice differentiable in a neighborhood of a stationary point , then:
★ If then has a maximum at .
★ If then has a minimum at .
★ If , the second derivative test says nothing about the point .
| Contents |
| Multivariable case |
| Concavity test |
| See also |
| References |
Multivariable case
Main articles: Second partial derivative test
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.
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.
Firstly, all points at which are found. In each of the intervals created, is then evaluated at a single point. For the intervals where the evaluated value of the function is concave down, and for all intervals between critical points where the evaluated value of the function is concave up. The points that separate intervals of opposing concavity are points of inflection.
See also
★ Fermat's theorem
★ First derivative test
★ Higher order derivative test
★ Differentiability
★ Extreme value
★ Inflection point
★ Convex function
★ Concave function
References
★ Second Derivative Test from 'Mathworld'
★ Concavity and the Second Derivative Test
★ Thomas Simpson's use of Second Derivative Test to Find Maxima and Minima at Convergence
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