HOME

TheInfoList



OR:

In
calculus Calculus, originally called infinitesimal calculus or "the calculus of infinitesimals", is the mathematical study of continuous change, in the same way that geometry is the study of shape, and algebra is the study of generalizations of arithm ...
, a derivative test uses the
derivative In mathematics, the derivative of a function of a real variable measures the sensitivity to change of the function value (output value) with respect to a change in its argument (input value). Derivatives are a fundamental tool of calculus. ...
s of a
function Function or functionality may refer to: Computing * Function key, a type of key on computer keyboards * Function model, a structured representation of processes in a system * Function object or functor or functionoid, a concept of object-oriente ...
to locate the critical points of a function and determine whether each point is a
local maximum In mathematical analysis, the maxima and minima (the respective plurals of maximum and minimum) of a function, known collectively as extrema (the plural of extremum), are the largest and smallest value of the function, either within a given ra ...
, a
local minimum In mathematical analysis, the maxima and minima (the respective plurals of maximum and minimum) of a function, known collectively as extrema (the plural of extremum), are the largest and smallest value of the function, either within a given ra ...
, or a saddle point. Derivative tests can also give information about the concavity of a function. The usefulness of derivatives to find extrema is proved mathematically by Fermat's theorem of stationary points.


First-derivative test

The first-derivative test examines a function's
monotonic In mathematics, a monotonic function (or monotone function) is a function between ordered sets that preserves or reverses the given order. This concept first arose in calculus, and was later generalized to the more abstract setting of ord ...
properties (where the function is increasing or decreasing), focusing on a particular point in its domain. If the function "switches" from increasing to decreasing at the point, then the function will achieve a highest value at that point. Similarly, if the function "switches" from decreasing to increasing at the point, then it will achieve a least value at that point. If the function fails to "switch" and remains increasing or remains decreasing, then no highest or least value is achieved. One can examine a function's monotonicity without calculus. However, calculus is usually helpful because there are sufficient conditions that guarantee the monotonicity properties above, and these conditions apply to the vast majority of functions one would encounter.


Precise statement of monotonicity properties

Stated precisely, suppose that ''f'' is a
real Real may refer to: Currencies * Brazilian real (R$) * Central American Republic real * Mexican real * Portuguese real * Spanish real * Spanish colonial real Music Albums * ''Real'' (L'Arc-en-Ciel album) (2000) * ''Real'' (Bright album) (2010) ...
-valued function defined on some open interval containing the point ''x'' and suppose further that ''f'' is
continuous Continuity or continuous may refer to: Mathematics * Continuity (mathematics), the opposing concept to discreteness; common examples include ** Continuous probability distribution or random variable in probability and statistics ** Continuous ...
at ''x''. * If there exists a positive number ''r'' > 0 such that ''f'' is weakly increasing on and weakly decreasing on , then ''f'' has a local maximum at ''x''. * If there exists a positive number ''r'' > 0 such that ''f'' is strictly increasing on and strictly increasing on , then ''f'' is strictly increasing on and does not have a local maximum or minimum at ''x''. Note that in the first case, ''f'' is not required to be strictly increasing or strictly decreasing to the left or right of ''x'', while in the last case, ''f'' is required to be strictly increasing or strictly decreasing. The reason is that in the definition of local maximum and minimum, the inequality is not required to be strict: e.g. every value of a constant function is considered both a local maximum and a local minimum.


Precise statement of first-derivative test

The first-derivative test depends on the "increasing–decreasing test", which is itself ultimately a consequence of the mean value theorem. It is a direct consequence of the way the
derivative In mathematics, the derivative of a function of a real variable measures the sensitivity to change of the function value (output value) with respect to a change in its argument (input value). Derivatives are a fundamental tool of calculus. ...
is defined and its connection to decrease and increase of a function locally, combined with the previous section. Suppose ''f'' is a real-valued function of a real variable defined on some interval containing the critical point ''a''. Further suppose that ''f'' is
continuous Continuity or continuous may refer to: Mathematics * Continuity (mathematics), the opposing concept to discreteness; common examples include ** Continuous probability distribution or random variable in probability and statistics ** Continuous ...
at ''a'' and
differentiable In mathematics, a differentiable function of one real variable is a function whose derivative exists at each point in its domain. In other words, the graph of a differentiable function has a non-vertical tangent line at each interior point in its ...
on some open interval containing ''a'', except possibly at ''a'' itself. * If there exists a positive number ''r'' > 0 such that for every ''x'' in (''a'' − ''r'', ''a'') we have and for every ''x'' in (''a'', ''a'' + ''r'') we have then ''f'' has a local maximum at ''a''. * If there exists a positive number ''r'' > 0 such that for every ''x'' in (''a'' − ''r'', ''a'') ∪ (''a'', ''a'' + ''r'') we have then ''f'' is strictly increasing at ''a'' and has neither a local maximum nor a local minimum there. * If none of the above conditions hold, then the test fails. (Such a condition is not vacuous; there are functions that satisfy none of the first three conditions, e.g. ''f''(''x'') = ''x''2 sin(1/''x'')). Again, corresponding to the comments in the section on monotonicity properties, note that in the first two cases, the inequality is not required to be strict, while in the next two, strict inequality is required.


Applications

The first-derivative test is helpful in solving
optimization problem In mathematics, computer science and economics, an optimization problem is the problem of finding the ''best'' solution from all feasible solutions. Optimization problems can be divided into two categories, depending on whether the variables ...
s in physics, economics, and engineering. In conjunction with the
extreme value theorem In calculus, the extreme value theorem states that if a real-valued function f is continuous on the closed interval ,b/math>, then f must attain a maximum and a minimum, each at least once. That is, there exist numbers c and d in ,b/math> su ...
, it can be used to find the absolute maximum and minimum of a real-valued function defined on a closed and bounded interval. In conjunction with other information such as concavity, inflection points, and
asymptote In analytic geometry, an asymptote () of a curve is a line such that the distance between the curve and the line approaches zero as one or both of the ''x'' or ''y'' coordinates tends to infinity. In projective geometry and related context ...
s, it can be used to sketch the
graph Graph may refer to: Mathematics *Graph (discrete mathematics), a structure made of vertices and edges **Graph theory, the study of such graphs and their properties *Graph (topology), a topological space resembling a graph in the sense of discre ...
of a function.


Second-derivative test (single variable)

After establishing the critical points of a function, the ''second-derivative test'' uses the value of the
second derivative In calculus, the second derivative, or the second order derivative, of a function is the derivative of the derivative of . Roughly speaking, the second derivative measures how the rate of change of a quantity is itself changing; for example, ...
at those points to determine whether such points are a local
maximum In mathematical analysis, the maxima and minima (the respective plurals of maximum and minimum) of a function, known collectively as extrema (the plural of extremum), are the largest and smallest value of the function, either within a given r ...
or a local
minimum In mathematical analysis, the maxima and minima (the respective plurals of maximum and minimum) of a function, known collectively as extrema (the plural of extremum), are the largest and smallest value of the function, either within a given r ...
. If the function ''f'' is twice-
differentiable In mathematics, a differentiable function of one real variable is a function whose derivative exists at each point in its domain. In other words, the graph of a differentiable function has a non-vertical tangent line at each interior point in its ...
at a critical point ''x'' (i.e. a point where '(''x'') = 0), then: * If f''(x) < 0, then f has a local maximum at x. * If f''(x) > 0, then f has a local minimum at x. * If f''(x) = 0, the test is inconclusive. In the last case,
Taylor's Theorem In calculus, Taylor's theorem gives an approximation of a ''k''-times differentiable function around a given point by a polynomial of degree ''k'', called the ''k''th-order Taylor polynomial. For a smooth function, the Taylor polynomial is th ...
may sometimes be used to determine the behavior of ''f'' near ''x'' using
higher derivative In mathematics, the derivative of a function of a real variable measures the sensitivity to change of the function value (output value) with respect to a change in its argument (input value). Derivatives are a fundamental tool of calculus. F ...
s.


Proof of the second-derivative test

Suppose we have f''(x) > 0 (the proof for f''(x) < 0 is analogous). By assumption, f'(x) = 0. Then : 0 < f''(x) = \lim_ \frac = \lim_ \frac. Thus, for ''h'' sufficiently small we get : \frac > 0, which means that f'(x + h) < 0 if h < 0 (intuitively, ''f'' is decreasing as it approaches x from the left), and that f'(x + h) > 0 if h > 0 (intuitively, ''f'' is increasing as we go right from ''x''). Now, by the first-derivative test, f has a local minimum at x.


Concavity test

A related but distinct use of second derivatives is to determine whether a function is concave up or
concave down In mathematics, a concave function is the negative of a convex function. A concave function is also synonymously called concave downwards, concave down, convex upwards, convex cap, or upper convex. Definition A real-valued function f on an in ...
at a point. It does not, however, provide information about inflection points. Specifically, a twice-differentiable function ''f'' is concave up if f''(x) > 0 and concave down if f''(x) < 0. Note that if f(x) = x^4, then x = 0 has zero second derivative, yet is not an inflection point, so the second derivative alone does not give enough information to determine whether a given point is an inflection point.


Higher-order derivative test

The ''higher-order derivative test'' or ''general derivative test'' is able to determine whether a function's critical points are maxima, minima, or points of inflection for a wider variety of functions than the second-order derivative test. As shown below, the second-derivative test is mathematically identical to the special case of ''n'' = 1 in the higher-order derivative test. Let ''f'' be a real-valued, sufficiently
differentiable function In mathematics, a differentiable function of one real variable is a function whose derivative exists at each point in its domain. In other words, the graph of a differentiable function has a non-vertical tangent line at each interior point in it ...
on an interval I \subset \R, let c \in I, and let n \ge 1 be a
natural number In mathematics, the natural numbers are those numbers used for counting (as in "there are ''six'' coins on the table") and ordering (as in "this is the ''third'' largest city in the country"). Numbers used for counting are called ''cardinal ...
. Also let all the derivatives of ''f'' at ''c'' be zero up to and including the ''n''-th derivative, but with the (''n'' + 1)th derivative being non-zero: : f'(c) = \cdots =f^(c) = 0\quad \text\quad f^(c) \ne 0. There are four possibilities, the first two cases where ''c'' is an extremum, the second two where ''c'' is a (local) saddle point: * If ''n'' is
odd Odd means unpaired, occasional, strange or unusual, or a person who is viewed as eccentric. Odd may also refer to: Acronym * ODD (Text Encoding Initiative) ("One Document Does it all"), an abstracted literate-programming format for describing X ...
and f^(c) < 0, then ''c'' is a local maximum. * If ''n'' is odd and f^(c) > 0, then ''c'' is a local minimum. * If ''n'' is
even Even may refer to: General * Even (given name), a Norwegian male personal name * Even (surname) * Even (people), an ethnic group from Siberia and Russian Far East ** Even language, a language spoken by the Evens * Odd and Even, a solitaire game w ...
and f^(c) < 0, then ''c'' is a strictly decreasing point of inflection. * If ''n'' is even and f^(c) > 0, then ''c'' is a strictly increasing point of inflection. Since ''n'' must be either odd or even, this analytical test classifies any stationary point of ''f'', so long as a nonzero derivative shows up eventually.


Example

Say we want to perform the general derivative test on the function f(x) = x^6 + 5 at the point x = 0. To do this, we calculate the derivatives of the function and then evaluate them at the point of interest until the result is nonzero. : f'(x) = 6x^5, f'(0) = 0; : f''(x) = 30x^4, f''(0) = 0; : f^(x) = 120x^3, f^(0) = 0; : f^(x) = 360x^2, f^(0) = 0; : f^(x) = 720x, f^(0) = 0; : f^(x) = 720, f^(0) = 720. As shown above, at the point x = 0, the function x^6 + 5 has all of its derivatives at 0 equal to 0, except for the 6th derivative, which is positive. Thus ''n'' = 5, and by the test, there is a local minimum at 0.


Multivariable case

For a function of more than one variable, the second-derivative test generalizes to a test based on the
eigenvalue In linear algebra, an eigenvector () or characteristic vector of a linear transformation is a nonzero vector that changes at most by a scalar factor when that linear transformation is applied to it. The corresponding eigenvalue, often denoted ...
s of the function's
Hessian matrix In mathematics, the Hessian matrix or Hessian is a square matrix of second-order partial derivatives of a scalar-valued function, or scalar field. It describes the local curvature of a function of many variables. The Hessian matrix was developed ...
at the critical point. In particular, assuming that all second-order partial derivatives of ''f'' are continuous on a
neighbourhood A neighbourhood (British English, Irish English, Australian English and Canadian English) or neighborhood (American English; American and British English spelling differences, see spelling differences) is a geographically localised community ...
of a critical 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.


See also

*
Fermat's theorem (stationary points) In mathematics, Fermat's theorem (also known as interior extremum theorem) is a method to find local maxima and minima of differentiable functions on open sets by showing that every local extremum of the function is a stationary point (the func ...
*
Maxima and minima In mathematical analysis, the maxima and minima (the respective plurals of maximum and minimum) of a function, known collectively as extrema (the plural of extremum), are the largest and smallest value of the function, either within a given ra ...
* Karush–Kuhn–Tucker conditions * Phase line – virtually identical diagram, used in the study of ordinary differential equations * Bordered Hessian *
Optimization (mathematics) Mathematical optimization (alternatively spelled ''optimisation'') or mathematical programming is the selection of a best element, with regard to some criterion, from some set of available alternatives. It is generally divided into two subfi ...
*
Differentiability In mathematics, a differentiable function of one real variable is a function whose derivative exists at each point in its domain. In other words, the graph of a differentiable function has a non- vertical tangent line at each interior point in ...
* Convex function * Second partial derivative test * Saddle point *
Inflection point In differential calculus and differential geometry, an inflection point, point of inflection, flex, or inflection (British English: inflexion) is a point on a smooth plane curve at which the curvature changes sign. In particular, in the case ...
*
Stationary point In mathematics, particularly in calculus, a stationary point of a differentiable function of one variable is a point on the graph of the function where the function's derivative is zero. Informally, it is a point where the function "stops" in ...


Further reading

* * * * *


References

{{reflist


External links


"Second Derivative Test" at Mathworld

Concavity and the Second Derivative Test

Thomas Simpson's use of Second Derivative Test to Find Maxima and Minima
at Convergence Differential calculus