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Differentiation

Derivative

f(x0)=limΔx0ΔyΔx=limΔx0f(x0+Δx)f(x0)Δxf'(x_0) = \lim\limits_{\Delta x \to 0} \dfrac{\Delta y}{\Delta x} = \lim\limits_{\Delta x \to 0} \dfrac{f(x_0 + \Delta x) - f(x_0)}{\Delta x}

f(x0)=limΔx0f(x0+Δx)f(x0)Δx=limxx0f(x)f(x0)xx0f'_-(x_0) = \lim\limits_{\Delta x \to 0^-} \dfrac{f(x_0 + \Delta x) - f(x_0)}{\Delta x} = \lim\limits_{x \to x_0^-} \dfrac{f(x) - f(x_0)}{x - x_0}

f+(x0)=limΔx0+f(x0+Δx)f(x0)Δx=limxx0+f(x)f(x0)xx0f'_+(x_0) = \lim\limits_{\Delta x \to 0^+} \dfrac{f(x_0 + \Delta x) - f(x_0)}{\Delta x} = \lim\limits_{x \to x_0^+} \dfrac{f(x) - f(x_0)}{x - x_0}

f(x0) exists    f(x)=f+(x)f'(x_0)\ exists \iff f'_-(x) = f'_+(x)

Algorithms

[f(x)±g(x)]=f(x)±g(x)[f(x) \pm g(x)]' = f'(x) \pm g'(x)

[f(x)g(x)]=f(x)g(x)+f(x)g(x)[f(x) \cdot g(x)]' = f'(x) \cdot g(x) + f(x) \cdot g'(x)

[f(x)g(x)]=f(x)g(x)f(x)g(x)[g(x)]2[\dfrac{f(x)}{g(x)}]' = \dfrac{f'(x) \cdot g(x) - f(x) \cdot g'(x)}{[g(x)]^2}

Differentiation Rules

(C)=0(C)' = 0

(xn)=nxn1\boxed{(x^n)' = nx^{n-1}}

(sinx)=cosx\boxed{(\sin x)' = \cos x}

(cosx)=sinx\boxed{(\cos x)' = -\sin x}

(tanx)=sec2x\boxed{(\tan x)' = \sec^2 x}

(secx)=secxtanx\boxed{(\sec x)' = \sec x \cdot \tan x}

(cotx)=csc2x(\cot x)' = - \csc^2 x

(cscx)=cscxcotx(\csc x)' = - \csc x \cdot \cot x

(ax)=axlna\boxed{(a^x)' = a^x \cdot \ln a}

(ex)=ex(e^x)' = e^x

(logax)=1xlna\boxed{(\log_ax)' = \frac{1}{x \cdot \ln a}}

(lnx)=1x(\ln x)' = \frac{1}{x}

The Chain Rule

(f(g(x)))=f(g(x))g(x)\boxed{(f(g(x)))' = f'(g(x)) \cdot g'(x)}

Inverse Functions

Inverse Functions

f1(f(x))=x    f(f1(x))=xf^{-1}(f(x)) = x \iff f(f^{-1}(x)) = x

if  g(x)=f1(x)\ g(x) = f^{-1}(x),

then  g(x)=1f(g(x)), f(g(x))0\ \boxed{g'(x) = \dfrac{1}{f'(g(x))}},\ f'(g(x)) \neq 0

L'Hôpital's Rule

when xax \to a,

if {f(x)0g(x)0 or{f(x)g(x)\left\{\begin{aligned} f(x) & \to 0 \\ g(x) & \to 0 \end{aligned}\right.\ or \left\{\begin{aligned} f(x) & \to \infty\\ g(x) & \to \infty \end{aligned}\right.,

then limxaf(x)g(x)=limxaf(x)g(x)\boxed{\lim\limits_{x \to a} \dfrac{f(x)}{g(x)} = \lim\limits_{x \to a} \dfrac{f'(x)}{g'(x)}}

Intermediate Value Theorem

If ff is continuous on [a,b][a, b], uu is a number such that min(f(a),f(b))<u<max(f(a),f(b))\min(f(a), f(b)) < u < \max(f(a), f(b)),

then there is a c(a,b)c \in (a, b) such that f(c)=uf(c) = u

Mean Value Theorem

If ff is continuous on [a,b][a, b] and differentiable on (a,b)(a, b), then

c(a,b)\exists c \in (a, b) such that f(c)=f(b)f(a)ba\boxed{f'(c) = \dfrac{f(b)-f(a)}{b-a}}

Extreme Value Theorem

If ff is continuous on the [a,b][a, b], then ff must attain a maximum and a minimum, each at least once, i.e.

c,d[a,b]\exists c, d \in [a, b] such that f(c)f(x)f(d),x[a,b]\boxed{f(c) \leq f(x) \leq f(d), \forall x \in [a, b]}

Concavity

  • If f>0\boxed{f'' > 0}, then ff concave up
  • If f<0\boxed{f'' < 0}, then ff concave down

Points of Inflection

{f=0 or DNEfchange sign\left\{\begin{aligned} f'' & = 0\ or\ DNE \\ f'' & change\ sign \end{aligned}\right.