Mean Value Theorem (Differentiation) : If f:[a,b]\to \mathbb{R}
is continuous on [a,b] and differentiable on (a,b) then
f(b)-f(a)=f^\prime(c)(b-a) for some c\in (a,b).
Mean Value Theorem (Integration): Assume that \int_a^b f(x)dx exists. Let M = \sup_{x \in [a,b]} f(x), m = \inf_{x \in [a,b]} f(x). Then there exists a real number c such that m \leq c \leq M and
\int_a^b f(x)dx = c(b-a)
If f is continuous on [a,b] then, c=f(x_0) for some x_0\in [a,b]
See Apostol for a Proof.
First Fundamental Theorem of Calculus: Assume that \int_a^b f(x)dx exists. Let F(x) = \int_a^x f(x)dx. Then F^\prime(x) exists at each point
x \in [a,b] where f is continuous.
For y\in (a,b) we have F(y+h) - F(y) = \int_y^{y+h} f(x)dx = c(y,h)h where \inf_{x \in [y,y+h]} f(x) \leq c(y,h) \leq \sup_{x \in [y,y+h]} f(x). Therefore, \frac{F(y+h) - F(y)}{h} = c(y,h). If f is continuous at y, then
both \inf_{x \in [y,y+h]} f(x) and \sup_{x \in [y,y+h]} f(x) converge to f(y)
as h \to 0. The same reasoning will give that
\frac{F(y)-F(y-h)}{h} also converges to f(y). Hence F^\prime(y) = f(y). For
the cases y=a,y=b, if we define one side limits of F, then clearly the above
reasoning applies and we get F^\prime(a)=f(a) and F^\prime(b)=f(b) if f is
continuous at a and b respectively. (Ofcourse, continuity is also one-sided here).
Second Fundamental Theorem of Calculus: Assume that
\int_a^b f(x)dx exists. Let g : [a,b] \to \mathbb{R} so that g^\prime(x) = f(x)
for all (a,b) and g(a) - g(a+) = g(b) - g(b-) (note that g(a+),g(b-) should exist). Then
\int_a^b f(x)dx = \int_a^b g^\prime(x)dx = g(b) - g(a)
Taylor's Theorm : Let f:[a,b] \to \mathbb{R} be such that f^{(n)} is finite on (a,b) and f^{(n-1)} is continuous on [a,b]. Assume that c\in [a,b]. Then
for every x \in [a,b], x\neq c there exits x_1 (which depends on x) interior to the interval joining x and c such that
f(x) = f(c) + \sum_{k=1}^{n-1}\frac{f^{(k)}(c)}{k!}(x-c)^k
+ \frac{f^{(n)}(x_1)}{n!}(x-c)^n
If it is known that f\in C^n[a,b] then Taylor's theorem gives a simple bounds
as f^{(n)} is bounded on [a,b]. A simple application of Taylor's theorem is given below. Suppose f\in C^2_b(\mathbb{R}) and we want to estimate the limit
\lim_{t \to 0} \frac{1}{\sqrt{2\pi}}\int_{-\infty}^\infty \frac{f(x+y\sqrt{t})-f(x)}{t}\exp{(-\frac{1}{2}y^2)}dy
Using Taylor's theorem, we can write f(x+y\sqrt{t}) = f(x) + f^{(1)}(x)y\sqrt{t} +\frac{f^{(2)}(x+\theta(y)\sqrt{t})}{2}ty^2. Therefore, the limit becomes
\lim_{t \to 0} \frac{1}{\sqrt{2\pi}}\int_{-\infty}^\infty \frac{f^{(1)}(x)y\sqrt{t} +\frac{f^{(2)}(x+\theta(y)\sqrt{t})}{2}ty^2}{t}\exp{(-\frac{1}{2}y^2)}dy
\lim_{t \to 0} \frac{1}{\sqrt{2\pi}}\int_{-\infty}^\infty \frac{f^{(2)}(x+\theta(y)\sqrt{t})}{2}y^2\exp{(-\frac{1}{2}y^2)}dy
Now, using dominated convergence (based on the fact that f^{(2)}(x) is bounded and
continuous), the limit can be pushed inside the integral. Finally we get that the
original expression equals
\frac{1}{2}f^{(2)}(x)
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