(mathematics) The proposition that, if a function ƒ(x) is continuous on the closed interval [a,b] and differentiable on the open interval (a,b), then there exists x0, a<x0<b, such that ƒ(b) - ƒ(a) = (b - a)ƒ′(x0). Also known as first law of the mean; Lagrange's formula; law of the mean.
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In calculus, the mean value theorem states, roughly: given an arc between two endpoints, there is at least one point at which the tangent to the arc is parallel to the secant through its endpoints.
The theorem is used to prove global statements about a function on an interval starting from local hypotheses about derivatives at points of the interval.
More precisely, if a function f(x) is continuous on the closed interval [a, b], where a < b, and differentiable on the open interval (a, b), then there exists a point c in (a, b) such that
This theorem can be understood intuitively by applying it to motion: If a car travels one hundred miles in one hour, then its average speed during that time was 100 miles per hour. To get at that average speed, the car either has to go at a constant 100 miles per hour during that whole time, or, if it goes slower at one moment, it has to go faster at another moment as well (and vice versa), in order to still end up with an average of 100 miles per hour. Therefore, the Mean Value Theorem tells us that at some point during the journey, the car must have been traveling at exactly 100 miles per hour; that is, it was traveling at its average speed.
A special case of this theorem was first described by Parameshvara (1370–1460) from the Kerala school of astronomy and mathematics in his commentaries on Govindasvāmi and Bhaskara II.[2] The mean value theorem in its modern form was later stated by Augustin Louis Cauchy (1789–1857). It is one of the most important results in differential calculus, as well as one of the most important theorems in mathematical analysis, and is essential in proving the fundamental theorem of calculus. The mean value theorem follows from the more specific statement of Rolle's theorem, and can be used to prove the more general statement of Taylor's theorem (with Lagrange form of the remainder term).
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Let f : [a, b] → R be a continuous function on the closed interval [a, b], and differentiable on the open interval (a, b), where a < b. Then there exists some c in (a, b) such that

The mean value theorem is a generalization of Rolle's theorem, which assumes f(a) = f(b), so that the right-hand side above is zero.
The mean value theorem is still valid in a slightly more general setting. One only needs to assume that f : [a, b] → R is continuous on [a, b], and that for every x in (a, b) the limit

exists as a finite number or equals +∞ or −∞. If finite, that limit equals f′(x). An example where this version of the theorem applies is given by the real-valued cube root function mapping x to x1/3, whose derivative tends to infinity at the origin.
Note that the theorem is false if a differentiable function is complex-valued instead of real-valued. For example, define f(x) = eix for all real x. Then
while |f′(x)| = 1.
The expression (f(b) − f(a)) / (b − a) gives the slope of the line joining the points (a, f(a)) and (b, f(b)), which is a chord of the graph of f, while f′(x) gives the slope of the tangent to the curve at the point (x, f(x)). Thus the Mean value theorem says that given any chord of a smooth curve, we can find a point lying between the end-points of the curve such that the tangent at that point is parallel to the chord. The following proof illustrates this idea.
Define g(x) = f(x) − rx, where r is a constant. Since f is continuous on [a, b] and differentiable on (a, b), the same is true for g. We now want to choose r so that g satisfies the conditions of Rolle's theorem. Namely

By Rolle's theorem, since g is continuous and g(a) = g(b), there is some c in (a, b) for which
, and it follows from the equality g(x) = f(x) − rx that,

as required.
Assume that f is a continuous, real-valued function, defined on an arbitrary interval I of the real line. If the derivative of f at every interior point of the interval I exists and is zero, then f is constant.
Proof: Assume the derivative of f at every interior point of the interval I exists and is zero. Let (a, b) be an arbitrary open interval in I. By the mean value theorem, there exists a point c in (a,b) such that

This implies that f(a) = f(b). Thus, f is constant on the interior of I and thus is constant on I by continuity. (See below for a multivariable version of this result.)
Remarks:
Cauchy's mean value theorem, also known as the extended mean value theorem, is a generalization of the mean value theorem. It states: If functions f and g are both continuous on the closed interval [a,b], and differentiable on the open interval (a, b), then there exists some c ∈ (a,b), such that

Of course, if g(a) ≠ g(b) and if g′(c) ≠ 0, this is equivalent to:

Geometrically, this means that there is some tangent to the graph of the curve
![\begin{array}{ccc}[a,b]&\longrightarrow&\mathbb{R}^2\\t&\mapsto&\bigl(f(t),g(t)\bigr),\end{array}](http://wpcontent.answcdn.com/wikipedia/en/math/4/6/2/462b9824ad88ae74d8f92a731bd39e0c.png)
which is parallel to the line defined by the points (f(a),g(a)) and (f(b),g(b)). However Cauchy's theorem does not claim the existence of such a tangent in all cases where (f(a),g(a)) and (f(b),g(b)) are distinct points, since it might be satisfied only for some value c with f′(c) = g′(c) = 0, in other words a value for which the mentioned curve is stationary; in such points no tangent to the curve is likely to be defined at all. An example of this situation is the curve given by

which on the interval [−1,1] goes from the point (−1,0) to (1,0), yet never has a horizontal tangent; however it has a stationary point (in fact a cusp) at t = 0.
Cauchy's mean value theorem can be used to prove l'Hôpital's rule. The mean value theorem is the special case of Cauchy's mean value theorem when g(t) = t.
The proof of Cauchy's mean value theorem is based on the same idea as the proof of the mean value theorem.
Define h(x) = f(x) − rg(x), where r is a constant. Since f and g are continuous on [a, b] and differentiable on (a, b), the same is true for h. We now want to choose r so that h satisfies the conditions of Rolle's theorem. Namely

By Rolle's theorem, since h is continuous and h(a) = h(b), there is some c in (a, b) for which
, and it follows from the equality h(x) = f(x) − rg(x) that,

as required.
The mean value theorem in one variable generalizes to several variables by applying the theorem in one variable via parametrization. Let G be an open subset of Rn, and let f : G → R be a differentiable function. Fix points x, y ∈ G such that the interval x y lies in G, and define g(t) = f((1 − t)x + ty). Since g is a differentiable function in one variable, the mean value theorem gives:

for some c between 0 and 1. But since g(1) = f(y) and g(0) = f(x), computing g′(c) explicitly we have:

where ∇ denotes a gradient and · a dot product. Note that this is an exact analog of the theorem in one variable (in the case n = 1 this is the theorem in one variable). By the Schwarz inequality, the equation gives the estimate:

In particular, when the partial derivatives of f are bounded, f is Lipschitz continuous (and therefore uniformly continuous). Note that f is not assumed to be continuously differentiable nor continuous on the closure of G. However, in the above, we used the chain rule so the existence of ∇f would not be sufficient.
As an application of the above, we prove that f is constant if G is connected and every partial derivative of f is 0. Pick some point x0 ∈ G, and let g(x) = f(x) − f(x0). We want to show g(x) = 0 for every x ∈ G. For that, let E = {x ∈ G : g(x) = 0} . Then E is closed and nonempty. It is open too: for every x ∈ E,

for every y in some neighborhood of x. (Here, it is crucial that x and y are sufficiently close to each other.) Since G is connected, we conclude E = G.
Remark that all arguments in the above are made in a coordinate-free manner; hence, they actually generalize to the case when G is a subset of a Banach space.
There is no exact analog of the mean value theorem for vector-valued functions. The problem is roughly speaking the following: If
is a differentiable function (where
is open) and if
is the line segment in question (lying inside
), then one can apply the above parametrization procedure to each of the component functions
of
(in the above notation set
). In doing so one finds points
on the line segment satisfying

But generally there will not be a single point
on the line segment satisfying

for all
simultaneously. (As a counterexample one could take
defined via the component functions
. Then
, but
and
are never simultaneously zero as
ranges over
.)
However a certain type of generalization of the mean value theorem to vector-valued functions is obtained as follows: Let f be a continuously differentiable real-valued function defined on an open interval I, and let x as well as x + h be points of I. The mean value theorem in one variable tells us that there exists some
between 0 and 1 such that

On the other hand we have, by the fundamental theorem of calculus followed by a change of variables,

Thus, the value
at the particular point
has been replaced by the mean value
. This last version can be generalized to vector valued functions:
Let
be open,
continuously differentiable, and
vectors such that the whole line segment
remains in
. Then we have:

where the integral of a matrix is to be understood componentwise. (Dƒ denotes the Jacobian matrix of ƒ.)
From this one can further deduce that if ||Dƒ(x + th)|| is bounded for t between 0 and 1 by some constant M, then

Proof of (*). Write
(
) for the real valued components of
. Define the functions
by 
Then we have

The claim follows since
is the matrix consisting of the components
, q.e.d.
Proof of (**). From (*) it follows that 
Here we have used the following
Lemma. Let
be a continuous function defined on the interval
. Then we have

Proof of (***). Let
denote the value of the integral
Now

thus
as desired. (Note the use of the Cauchy–Schwarz inequality.) This shows (***) and thereby finishes the proof of (**).
The first mean value theorem for integration states
is a continuous function and
is an integrable function that does not change sign on the interval
, then there exists a number
such that
In particular, if
for all
, then there exists
such that

The point
is called the mean value of
on
.
It follows from the extreme value theorem that the continuous function G has a finite infimum m and a finite supremum M on the interval [a, b]. From the monotonicity of the integral and the fact that m ≤ G(t) ≤ M, it follows that

where

denotes the integral of
. Hence, if I = 0, then the claimed equality holds for every x in [a, b]. Therefore, we may assume I > 0 in the following. Dividing through by I we have that

The extreme value theorem tells us more than just that the infimum and supremum of G on [a, b] are finite; it tells us that both are actually attained. Thus we can apply the intermediate value theorem, and conclude that the continuous function G attains every value of the interval [m, M], in particular there exists x in [a, b] such that

This completes the proof.
There are various slightly different theorems called the second mean value theorem for integration. A commonly found version is as follows:

Here G(a + 0) stands for
, the existence of which follows from the conditions. Note that it is essential that the interval (a, b] contains b. A variant not having this requirement is:

This variant was proved by Hiroshi Okamura in 1947.[citation needed]
Let
and
be non-negative random variables such that
and
(i.e.
is smaller than
in the usual stochastic order). Then there exists an absolutely continuous non-negative random variable
having probability density function

Let
be a measurable and differentiable function such that
and
are finite, and let its derivative
be measurable and Riemann-integrable on the interval
for all
. Then,
is finite and[3]
![{\rm E}[g(Y)]-{\rm E}[g(X)]={\rm E}[g'(Z)]\,[{\rm E}(Y)-{\rm E}(X)].](http://wpcontent.answcdn.com/wikipedia/en/math/2/9/8/2986d39dbc3b25b9dbb247624e2d97ec.png)
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