Antiderivatives and Indefinite Integrals Definition of Antiderivative : Given a function f ( x ) f(x) f ( x ) , an antiderivative of f ( x ) f(x) f ( x ) is a function F ( x ) F(x) F ( x ) such that F ′ ( x ) = f ( x ) F'(x) = f(x) F ′ ( x ) = f ( x ) .Example : Since d d x ( x 5 ) = 5 x 4 \frac{d}{dx}(x^5) = 5x^4 d x d ( x 5 ) = 5 x 4 , an antiderivative of 5 x 4 5x^4 5 x 4 is x 5 x^5 x 5 .Indefinite Integral Notation : If F ′ ( x ) = f ( x ) F'(x) = f(x) F ′ ( x ) = f ( x ) , then ∫ f ( x ) d x = F ( x ) + C \int f(x)\,dx = F(x) + C ∫ f ( x ) d x = F ( x ) + C .Role of the Arbitrary Constant C C C : The constant C C C records all possible antiderivatives of f ( x ) f(x) f ( x ) . It is not a decorative symbol; because the derivative of any constant is zero, d d x ( F ( x ) + C ) = F ′ ( x ) + 0 = f ( x ) \frac{d}{dx}(F(x) + C) = F'(x) + 0 = f(x) d x d ( F ( x ) + C ) = F ′ ( x ) + 0 = f ( x ) .Uniqueness Up to a Constant : Suppose F ′ ( x ) = G ′ ( x ) F'(x) = G'(x) F ′ ( x ) = G ′ ( x ) on an interval. Then d d x ( F ( x ) − G ( x ) ) = 0 \frac{d}{dx}(F(x) - G(x)) = 0 d x d ( F ( x ) − G ( x )) = 0 . By the Mean Value Theorem, F ( x ) − G ( x ) = C F(x) - G(x) = C F ( x ) − G ( x ) = C for some constant C C C . Consequently, on an interval, all antiderivatives of a given function differ by a constant.Visual Interpretation : Integration operates as the inverse process of differentiation.
Linearity Rules : Antiderivatives satisfy linearity properties:∫ ( a f ( x ) + b g ( x ) ) d x = a ∫ f ( x ) d x + b ∫ g ( x ) d x \int (a f(x) + b g(x))\,dx = a \int f(x)\,dx + b \int g(x)\,dx ∫ ( a f ( x ) + b g ( x )) d x = a ∫ f ( x ) d x + b ∫ g ( x ) d x Example : ∫ ( 6 x 2 − 4 x + 7 ) d x = 2 x 3 − 2 x 2 + 7 x + C \int (6x^2 - 4x + 7)\,dx = 2x^3 - 2x^2 + 7x + C ∫ ( 6 x 2 − 4 x + 7 ) d x = 2 x 3 − 2 x 2 + 7 x + C Power Rule for Antiderivatives : For any real exponent n ≠ − 1 n \neq -1 n = − 1 :∫ x n d x = x n + 1 n + 1 + C \int x^n\,dx = \frac{x^{n+1}}{n+1} + C ∫ x n d x = n + 1 x n + 1 + C Example 1 : ∫ x 7 d x = x 8 8 + C \int x^7\,dx = \frac{x^8}{8} + C ∫ x 7 d x = 8 x 8 + C Example 2 : ∫ x d x = ∫ x 1 / 2 d x = 2 3 x 3 / 2 + C \int \sqrt{x}\,dx = \int x^{1/2}\,dx = \frac{2}{3}x^{3/2} + C ∫ x d x = ∫ x 1/2 d x = 3 2 x 3/2 + C The Exceptional Power n = − 1 n = -1 n = − 1 : The standard power rule fails when n = − 1 n = -1 n = − 1 because it produces division by zero. Instead:∫ 1 x d x = ln ( ∣ x ∣ ) + C \int \frac{1}{x}\,dx = \ln(|x|) + C ∫ x 1 d x = ln ( ∣ x ∣ ) + C Reason : d d x ln ( ∣ x ∣ ) = 1 x \frac{d}{dx}\ln(|x|) = \frac{1}{x} d x d ln ( ∣ x ∣ ) = x 1 for all x ≠ 0 x \neq 0 x = 0 Fundamental Table of Exponential and Logarithmic Antiderivatives :∫ e x d x = e x + C \int e^x\,dx = e^x + C ∫ e x d x = e x + C ∫ a x d x = a x ln ( a ) + C \int a^x\,dx = \frac{a^x}{\ln(a)} + C ∫ a x d x = l n ( a ) a x + C for a > 0 , a ≠ 1 a > 0, a \neq 1 a > 0 , a = 1 ∫ 1 x d x = ln ( ∣ x ∣ ) + C \int \frac{1}{x}\,dx = \ln(|x|) + C ∫ x 1 d x = ln ( ∣ x ∣ ) + C ∫ u ′ ( x ) u ( x ) d x = ln ( ∣ u ( x ) ∣ ) + C \int \frac{u'(x)}{u(x)}\,dx = \ln(|u(x)|) + C ∫ u ( x ) u ′ ( x ) d x = ln ( ∣ u ( x ) ∣ ) + C Fundamental Table of Trigonometric Antiderivatives :∫ cos ( x ) d x = sin ( x ) + C \int \cos(x)\,dx = \sin(x) + C ∫ cos ( x ) d x = sin ( x ) + C ∫ sin ( x ) d x = − cos ( x ) + C \int \sin(x)\,dx = -\cos(x) + C ∫ sin ( x ) d x = − cos ( x ) + C ∫ sec 2 ( x ) d x = tan ( x ) + C \int \sec^2(x)\,dx = \tan(x) + C ∫ sec 2 ( x ) d x = tan ( x ) + C ∫ csc 2 ( x ) d x = − cot ( x ) + C \int \csc^2(x)\,dx = -\cot(x) + C ∫ csc 2 ( x ) d x = − cot ( x ) + C ∫ sec ( x ) tan ( x ) d x = sec ( x ) + C \int \sec(x)\tan(x)\,dx = \sec(x) + C ∫ sec ( x ) tan ( x ) d x = sec ( x ) + C ∫ csc ( x ) cot ( x ) d x = − csc ( x ) + C \int \csc(x)\cot(x)\,dx = -\csc(x) + C ∫ csc ( x ) cot ( x ) d x = − csc ( x ) + C Inverse Trigonometric Antiderivatives :∫ d x 1 + x 2 = arctan ( x ) + C \int \frac{dx}{1 + x^2} = \arctan(x) + C ∫ 1 + x 2 d x = arctan ( x ) + C ∫ d x 1 − x 2 = arcsin ( x ) + C \int \frac{dx}{\sqrt{1 - x^2}} = \arcsin(x) + C ∫ 1 − x 2 d x = arcsin ( x ) + C General Form : ∫ d x a 2 + x 2 = 1 a arctan ( x a ) + C \int \frac{dx}{a^2 + x^2} = \frac{1}{a}\arctan\left(\frac{x}{a}\right) + C ∫ a 2 + x 2 d x = a 1 arctan ( a x ) + C for a > 0 a > 0 a > 0 Basic Integration Examples :∫ ( 4 x 3 − 3 x + 5 e x ) d x = x 4 − 3 ln ( ∣ x ∣ ) + 5 e x + C \int \left(4x^3 - \frac{3}{x} + 5e^x\right)\,dx = x^4 - 3\ln(|x|) + 5e^x + C ∫ ( 4 x 3 − x 3 + 5 e x ) d x = x 4 − 3 ln ( ∣ x ∣ ) + 5 e x + C ∫ ( 2 cos ( x ) − 7 sec 2 ( x ) ) d x = 2 sin ( x ) − 7 tan ( x ) + C \int \left(2\cos(x) - 7\sec^2(x)\right)\,dx = 2\sin(x) - 7\tan(x) + C ∫ ( 2 cos ( x ) − 7 sec 2 ( x ) ) d x = 2 sin ( x ) − 7 tan ( x ) + C Verification Habit : The fastest method to detect integration errors is differentiating the anti-derivative result:d d x ( 2 3 x 3 / 2 + C ) = 2 3 ⋅ 3 2 x 1 / 2 + 0 = x 1 / 2 = x \frac{d}{dx}\left(\frac{2}{3}x^{3/2} + C\right) = \frac{2}{3}\cdot\frac{3}{2}x^{1/2} + 0 = x^{1/2} = \sqrt{x} d x d ( 3 2 x 3/2 + C ) = 3 2 ⋅ 2 3 x 1/2 + 0 = x 1/2 = x The Substitution Method for Integration Theoretical Principle : The substitution rule reverses the chain rule of differentiation. If u = g ( x ) u = g(x) u = g ( x ) , then d u = g ′ ( x ) d x du = g'(x)\,dx d u = g ′ ( x ) d x , transforming the integral:∫ f ( g ( x ) ) g ′ ( x ) d x = ∫ f ( u ) d u \int f(g(x))g'(x)\,dx = \int f(u)\,du ∫ f ( g ( x )) g ′ ( x ) d x = ∫ f ( u ) d u After computing the antiderivative in terms of u u u , substitute back u = g ( x ) u = g(x) u = g ( x ) . Guidelines for Choosing u u u :An expression situated inside a power, radical, exponential, logarithm, or trigonometric function. A denominator whose derivative (up to a constant multiple) appears in the numerator. A complicated expression whose derivative almost appears in the integrand. Warning : If d u du d u does not match the remaining algebraic factors, substitution will not resolve the integral.Direct Substitution Example : Evaluate ∫ 2 x cos ( x 2 + 1 ) d x \int 2x\cos(x^2 + 1)\,dx ∫ 2 x cos ( x 2 + 1 ) d x Let u = x 2 + 1 u = x^2 + 1 u = x 2 + 1 , then d u = 2 x d x du = 2x\,dx d u = 2 x d x ∫ cos ( u ) d u = sin ( u ) + C = sin ( x 2 + 1 ) + C \int \cos(u)\,du = \sin(u) + C = \sin(x^2 + 1) + C ∫ cos ( u ) d u = sin ( u ) + C = sin ( x 2 + 1 ) + C Constant Adjustment Example : Evaluate ∫ x x 2 + 4 d x \int x\sqrt{x^2 + 4}\,dx ∫ x x 2 + 4 d x Let u = x 2 + 4 u = x^2 + 4 u = x 2 + 4 , then d u = 2 x d x ⟹ x d x = 1 2 d u du = 2x\,dx \implies x\,dx = \frac{1}{2}du d u = 2 x d x ⟹ x d x = 2 1 d u 1 2 ∫ u 1 / 2 d u = 1 2 ⋅ 2 3 u 3 / 2 + C = 1 3 ( x 2 + 4 ) 3 / 2 + C \frac{1}{2}\int u^{1/2}\,du = \frac{1}{2}\cdot\frac{2}{3}u^{3/2} + C = \frac{1}{3}(x^2 + 4)^{3/2} + C 2 1 ∫ u 1/2 d u = 2 1 ⋅ 3 2 u 3/2 + C = 3 1 ( x 2 + 4 ) 3/2 + C Logarithmic Form Example : Evaluate ∫ 3 x 2 x 3 + 5 d x \int \frac{3x^2}{x^3 + 5}\,dx ∫ x 3 + 5 3 x 2 d x Let u = x 3 + 5 u = x^3 + 5 u = x 3 + 5 , then d u = 3 x 2 d x du = 3x^2\,dx d u = 3 x 2 d x ∫ d u u = ln ( ∣ u ∣ ) + C = ln ( ∣ x 3 + 5 ∣ ) + C \int \frac{du}{u} = \ln(|u|) + C = \ln(|x^3 + 5|) + C ∫ u d u = ln ( ∣ u ∣ ) + C = ln ( ∣ x 3 + 5∣ ) + C Definite Integrals by Substitution : When evaluating a definite integral via substitution, the integration limits must be converted to the variable u u u :∫ a b f ( g ( x ) ) g ′ ( x ) d x = ∫ g ( a ) g ( b ) f ( u ) d u \int_a^b f(g(x))g'(x)\,dx = \int_{g(a)}^{g(b)} f(u)\,du ∫ a b f ( g ( x )) g ′ ( x ) d x = ∫ g ( a ) g ( b ) f ( u ) d u Safe Method 1 : Convert limits to u u u and evaluate entirely in terms of u u u .Safe Method 2 : Find the antiderivative in terms of x x x and evaluate using original limits a a a and b b b Definite Integral Example : Evaluate ∫ 0 2 x x 2 + 1 d x \int_0^2 x\sqrt{x^2 + 1}\,dx ∫ 0 2 x x 2 + 1 d x Let u = x 2 + 1 u = x^2 + 1 u = x 2 + 1 , d u = 2 x d x ⟹ x d x = 1 2 d u du = 2x\,dx \implies x\,dx = \frac{1}{2}du d u = 2 x d x ⟹ x d x = 2 1 d u Convert limits: When x = 0 x = 0 x = 0 , u = 0 2 + 1 = 1 u = 0^2 + 1 = 1 u = 0 2 + 1 = 1 . When x = 2 x = 2 x = 2 , u = 2 2 + 1 = 5 u = 2^2 + 1 = 5 u = 2 2 + 1 = 5 1 2 ∫ 1 5 u 1 / 2 d u = 1 2 [ 2 3 u 3 / 2 ] 1 5 = 1 3 ( 5 3 / 2 − 1 3 / 2 ) = 5 5 − 1 3 \frac{1}{2}\int_1^5 u^{1/2}\,du = \frac{1}{2}\left[\frac{2}{3}u^{3/2}\right]_1^5 = \frac{1}{3}\left(5^{3/2} - 1^{3/2}\right) = \frac{5\sqrt{5} - 1}{3} 2 1 ∫ 1 5 u 1/2 d u = 2 1 [ 3 2 u 3/2 ] 1 5 = 3 1 ( 5 3/2 − 1 3/2 ) = 3 5 5 − 1 Mixed Variables Error : A u u u -integral must never retain remaining factors of x x x . For example, transforming ∫ x x 2 + 4 d x \int x\sqrt{x^2 + 4}\,dx ∫ x x 2 + 4 d x into ∫ x u d u \int x\sqrt{u}\,du ∫ x u d u is mathematically invalid.Advanced and Challenging Integration Techniques Root Substitution Technique : Evaluate ∫ e 2 x e x + 1 4 d x \int \frac{e^{2x}}{\sqrt[4]{e^x + 1}}\,dx ∫ 4 e x + 1 e 2 x d x Set e x + 1 = t 4 ⟹ e x = t 4 − 1 e^x + 1 = t^4 \implies e^x = t^4 - 1 e x + 1 = t 4 ⟹ e x = t 4 − 1 and e 2 x = ( t 4 − 1 ) 2 e^{2x} = (t^4 - 1)^2 e 2 x = ( t 4 − 1 ) 2 Differentiate e x + 1 = t 4 e^x + 1 = t^4 e x + 1 = t 4 to get e x d x = 4 t 3 d t ⟹ d x = 4 t 3 e x d t = 4 t 3 t 4 − 1 d t e^x\,dx = 4t^3\,dt \implies dx = \frac{4t^3}{e^x}\,dt = \frac{4t^3}{t^4 - 1}\,dt e x d x = 4 t 3 d t ⟹ d x = e x 4 t 3 d t = t 4 − 1 4 t 3 d t Substitute into integral: ∫ ( t 4 − 1 ) 2 t ⋅ 4 t 3 t 4 − 1 d t = 4 ∫ t 2 ( t 4 − 1 ) d t = 4 ∫ ( t 6 − t 2 ) d t \int \frac{(t^4 - 1)^2}{t}\cdot\frac{4t^3}{t^4 - 1}\,dt = 4\int t^2(t^4 - 1)\,dt = 4\int (t^6 - t^2)\,dt ∫ t ( t 4 − 1 ) 2 ⋅ t 4 − 1 4 t 3 d t = 4 ∫ t 2 ( t 4 − 1 ) d t = 4 ∫ ( t 6 − t 2 ) d t Integrate: 4 ( t 7 7 − t 3 3 ) + C = 4 7 t 7 − 4 3 t 3 + C 4\left(\frac{t^7}{7} - \frac{t^3}{3}\right) + C = \frac{4}{7}t^7 - \frac{4}{3}t^3 + C 4 ( 7 t 7 − 3 t 3 ) + C = 7 4 t 7 − 3 4 t 3 + C Substitute back t = ( e x + 1 ) 1 / 4 t = (e^x + 1)^{1/4} t = ( e x + 1 ) 1/4 : 4 7 ( e x + 1 ) 7 / 4 − 4 3 ( e x + 1 ) 3 / 4 + C \frac{4}{7}(e^x + 1)^{7/4} - \frac{4}{3}(e^x + 1)^{3/4} + C 7 4 ( e x + 1 ) 7/4 − 3 4 ( e x + 1 ) 3/4 + C Trigonometric-Rational Integral : Evaluate ∫ d x 2 cos 2 ( x ) + 5 sin 2 ( x ) \int \frac{dx}{2\cos^2(x) + 5\sin^2(x)} ∫ 2 c o s 2 ( x ) + 5 s i n 2 ( x ) d x Set t = tan ( x ) ⟹ d t = sec 2 ( x ) d x = ( 1 + t 2 ) d x ⟹ d x = d t 1 + t 2 t = \tan(x) \implies dt = \sec^2(x)\,dx = (1 + t^2)\,dx \implies dx = \frac{dt}{1 + t^2} t = tan ( x ) ⟹ d t = sec 2 ( x ) d x = ( 1 + t 2 ) d x ⟹ d x = 1 + t 2 d t Express trigonometric powers in terms of t t t :cos 2 ( x ) = 1 1 + t 2 \cos^2(x) = \frac{1}{1 + t^2} cos 2 ( x ) = 1 + t 2 1 sin 2 ( x ) = t 2 1 + t 2 \sin^2(x) = \frac{t^2}{1 + t^2} sin 2 ( x ) = 1 + t 2 t 2 Rewrite denominator: 2 cos 2 ( x ) + 5 sin 2 ( x ) = 2 + 5 t 2 1 + t 2 2\cos^2(x) + 5\sin^2(x) = \frac{2 + 5t^2}{1 + t^2} 2 cos 2 ( x ) + 5 sin 2 ( x ) = 1 + t 2 2 + 5 t 2 Substitute: ∫ d t 1 + t 2 2 + 5 t 2 1 + t 2 = ∫ d t 2 + 5 t 2 = 1 2 ∫ d t 1 + ( 5 2 t ) 2 \int \frac{\frac{dt}{1 + t^2}}{\frac{2 + 5t^2}{1 + t^2}} = \int \frac{dt}{2 + 5t^2} = \frac{1}{2}\int \frac{dt}{1 + \left(\sqrt{\frac{5}{2}}t\right)^2} ∫ 1 + t 2 2 + 5 t 2 1 + t 2 d t = ∫ 2 + 5 t 2 d t = 2 1 ∫ 1 + ( 2 5 t ) 2 d t Integrate: 1 2 ⋅ 1 5 2 arctan ( 5 2 t ) + C = 1 10 arctan ( 5 2 t ) + C \frac{1}{2}\cdot\frac{1}{\sqrt{\frac{5}{2}}}\arctan\left(\sqrt{\frac{5}{2}}t\right) + C = \frac{1}{\sqrt{10}}\arctan\left(\sqrt{\frac{5}{2}}t\right) + C 2 1 ⋅ 2 5 1 arctan ( 2 5 t ) + C = 10 1 arctan ( 2 5 t ) + C Substitute back t = tan ( x ) t = \tan(x) t = tan ( x ) : 1 10 arctan ( 5 2 tan ( x ) ) + C \frac{1}{\sqrt{10}}\arctan\left(\sqrt{\frac{5}{2}}\tan(x)\right) + C 10 1 arctan ( 2 5 tan ( x ) ) + C Algebraic Power-Root Integral : Evaluate ∫ x 7 1 + x 2 4 d x \int \frac{x^7}{\sqrt[4]{1 + x^2}}\,dx ∫ 4 1 + x 2 x 7 d x Let 1 + x 2 = t 4 ⟹ x 2 = t 4 − 1 1 + x^2 = t^4 \implies x^2 = t^4 - 1 1 + x 2 = t 4 ⟹ x 2 = t 4 − 1 and 2 x d x = 4 t 3 d t ⟹ x d x = 2 t 3 d t 2x\,dx = 4t^3\,dt \implies x\,dx = 2t^3\,dt 2 x d x = 4 t 3 d t ⟹ x d x = 2 t 3 d t Decompose numerator: x 7 d x = ( x 2 ) 3 ( x d x ) = ( t 4 − 1 ) 3 ( 2 t 3 d t ) x^7\,dx = (x^2)^3(x\,dx) = (t^4 - 1)^3 (2t^3\,dt) x 7 d x = ( x 2 ) 3 ( x d x ) = ( t 4 − 1 ) 3 ( 2 t 3 d t ) Substitute: ∫ ( t 4 − 1 ) 3 ⋅ 2 t 3 d t t = 2 ∫ t 2 ( t 4 − 1 ) 3 d t \int \frac{(t^4 - 1)^3\cdot 2t^3\,dt}{t} = 2\int t^2(t^4 - 1)^3\,dt ∫ t ( t 4 − 1 ) 3 ⋅ 2 t 3 d t = 2 ∫ t 2 ( t 4 − 1 ) 3 d t Expand ( t 4 − 1 ) 3 = t 12 − 3 t 8 + 3 t 4 − 1 (t^4 - 1)^3 = t^{12} - 3t^8 + 3t^4 - 1 ( t 4 − 1 ) 3 = t 12 − 3 t 8 + 3 t 4 − 1 :2 ∫ t 2 ( t 12 − 3 t 8 + 3 t 4 − 1 ) d t = 2 ∫ ( t 14 − 3 t 10 + 3 t 6 − t 2 ) d t 2\int t^2(t^{12} - 3t^8 + 3t^4 - 1)\,dt = 2\int (t^{14} - 3t^{10} + 3t^6 - t^2)\,dt 2 ∫ t 2 ( t 12 − 3 t 8 + 3 t 4 − 1 ) d t = 2 ∫ ( t 14 − 3 t 10 + 3 t 6 − t 2 ) d t Integrate: 2 ( t 15 15 − 3 t 11 11 + 3 t 7 7 − t 3 3 ) + C 2\left(\frac{t^{15}}{15} - \frac{3t^{11}}{11} + \frac{3t^7}{7} - \frac{t^3}{3}\right) + C 2 ( 15 t 15 − 11 3 t 11 + 7 3 t 7 − 3 t 3 ) + C Substitute back t = ( 1 + x 2 ) 1 / 4 t = (1 + x^2)^{1/4} t = ( 1 + x 2 ) 1/4 . 2 15 ( 1 + x 2 ) 15 / 4 − 6 11 ( 1 + x 2 ) 11 / 4 + 6 7 ( 1 + x 2 ) 7 / 4 − 2 3 ( 1 + x 2 ) 3 / 4 + C \frac{2}{15}(1 + x^2)^{15/4} - \frac{6}{11}(1 + x^2)^{11/4} + \frac{6}{7}(1 + x^2)^{7/4} - \frac{2}{3}(1 + x^2)^{3/4} + C 15 2 ( 1 + x 2 ) 15/4 − 11 6 ( 1 + x 2 ) 11/4 + 7 6 ( 1 + x 2 ) 7/4 − 3 2 ( 1 + x 2 ) 3/4 + C Logarithmic-Root Integral : Evaluate ∫ ( ln ( x ) ) 2 x 2 + ln ( x ) 3 d x \int \frac{(\ln(x))^2}{x\sqrt[3]{2 + \ln(x)}}\,dx ∫ x 3 2 + l n ( x ) ( l n ( x ) ) 2 d x for x > e − 2 x > e^{-2} x > e − 2 Set 2 + ln ( x ) = t 3 ⟹ ln ( x ) = t 3 − 2 2 + \ln(x) = t^3 \implies \ln(x) = t^3 - 2 2 + ln ( x ) = t 3 ⟹ ln ( x ) = t 3 − 2 and d x x = 3 t 2 d t \frac{dx}{x} = 3t^2\,dt x d x = 3 t 2 d t Substitute: ∫ ( t 3 − 2 ) 2 t ⋅ 3 t 2 d t = 3 ∫ t ( t 3 − 2 ) 2 d t = 3 ∫ t ( t 6 − 4 t 3 + 4 ) d t = 3 ∫ ( t 7 − 4 t 4 + 4 t ) d t \int \frac{(t^3 - 2)^2}{t}\cdot 3t^2\,dt = 3\int t(t^3 - 2)^2\,dt = 3\int t(t^6 - 4t^3 + 4)\,dt = 3\int (t^7 - 4t^4 + 4t)\,dt ∫ t ( t 3 − 2 ) 2 ⋅ 3 t 2 d t = 3 ∫ t ( t 3 − 2 ) 2 d t = 3 ∫ t ( t 6 − 4 t 3 + 4 ) d t = 3 ∫ ( t 7 − 4 t 4 + 4 t ) d t Integrate: 3 ( t 8 8 − 4 t 5 5 + 2 t 2 ) + C = 3 8 t 8 − 12 5 t 5 + 6 t 2 + C 3\left(\frac{t^8}{8} - \frac{4t^5}{5} + 2t^2\right) + C = \frac{3}{8}t^8 - \frac{12}{5}t^5 + 6t^2 + C 3 ( 8 t 8 − 5 4 t 5 + 2 t 2 ) + C = 8 3 t 8 − 5 12 t 5 + 6 t 2 + C Substitute back t = ( 2 + ln ( x ) ) 1 / 3 t = (2 + \ln(x))^{1/3} t = ( 2 + ln ( x ) ) 1/3 . 3 8 ( 2 + ln ( x ) ) 8 / 3 − 12 5 ( 2 + ln ( x ) ) 5 / 3 + 6 ( 2 + ln ( x ) ) 2 / 3 + C \frac{3}{8}(2 + \ln(x))^{8/3} - \frac{12}{5}(2 + \ln(x))^{5/3} + 6(2 + \ln(x))^{2/3} + C 8 3 ( 2 + ln ( x ) ) 8/3 − 5 12 ( 2 + ln ( x ) ) 5/3 + 6 ( 2 + ln ( x ) ) 2/3 + C Radicand Denominator Integral : Evaluate ∫ x 3 x 2 + 1 + 1 d x \int \frac{x^3}{\sqrt{x^2 + 1} + 1}\,dx ∫ x 2 + 1 + 1 x 3 d x Set u = x 2 + 1 + 1 ⟹ u − 1 = x 2 + 1 ⟹ ( u − 1 ) 2 = x 2 + 1 ⟹ x 2 = u 2 − 2 u u = \sqrt{x^2 + 1} + 1 \implies u - 1 = \sqrt{x^2 + 1} \implies (u - 1)^2 = x^2 + 1 \implies x^2 = u^2 - 2u u = x 2 + 1 + 1 ⟹ u − 1 = x 2 + 1 ⟹ ( u − 1 ) 2 = x 2 + 1 ⟹ x 2 = u 2 − 2 u Differentiate x 2 = u 2 − 2 u ⟹ 2 x d x = ( 2 u − 2 ) d u ⟹ x d x = ( u − 1 ) d u x^2 = u^2 - 2u \implies 2x\,dx = (2u - 2)\,du \implies x\,dx = (u - 1)\,du x 2 = u 2 − 2 u ⟹ 2 x d x = ( 2 u − 2 ) d u ⟹ x d x = ( u − 1 ) d u Decompose x 3 d x = x 2 ( x d x ) = ( u 2 − 2 u ) ( u − 1 ) d u x^3\,dx = x^2(x\,dx) = (u^2 - 2u)(u - 1)\,du x 3 d x = x 2 ( x d x ) = ( u 2 − 2 u ) ( u − 1 ) d u Substitute: ∫ ( u 2 − 2 u ) ( u − 1 ) u d u = ∫ ( u − 2 ) ( u − 1 ) d u = ∫ ( u 2 − 3 u + 2 ) d u \int \frac{(u^2 - 2u)(u - 1)}{u}\,du = \int (u - 2)(u - 1)\,du = \int (u^2 - 3u + 2)\,du ∫ u ( u 2 − 2 u ) ( u − 1 ) d u = ∫ ( u − 2 ) ( u − 1 ) d u = ∫ ( u 2 − 3 u + 2 ) d u Integrate: u 3 3 − 3 u 2 2 + 2 u + C \frac{u^3}{3} - \frac{3u^2}{2} + 2u + C 3 u 3 − 2 3 u 2 + 2 u + C Substitute back u = x 2 + 1 + 1 u = \sqrt{x^2 + 1} + 1 u = x 2 + 1 + 1 ( x 2 + 1 + 1 ) 3 3 − 3 ( x 2 + 1 + 1 ) 2 2 + 2 ( x 2 + 1 + 1 ) + C \frac{(\sqrt{x^2 + 1} + 1)^3}{3} - \frac{3(\sqrt{x^2 + 1} + 1)^2}{2} + 2(\sqrt{x^2 + 1} + 1) + C 3 ( x 2 + 1 + 1 ) 3 − 2 3 ( x 2 + 1 + 1 ) 2 + 2 ( x 2 + 1 + 1 ) + C Rational Quadratic Square Integral : Evaluate ∫ x 3 ( x 2 + 2 x + 2 ) 2 d x \int \frac{x^3}{(x^2 + 2x + 2)^2}\,dx ∫ ( x 2 + 2 x + 2 ) 2 x 3 d x Complete the square: x 2 + 2 x + 2 = ( x + 1 ) 2 + 1 x^2 + 2x + 2 = (x + 1)^2 + 1 x 2 + 2 x + 2 = ( x + 1 ) 2 + 1 Set u = x + 1 ⟹ x = u − 1 , d x = d u , x 2 + 2 x + 2 = u 2 + 1 u = x + 1 \implies x = u - 1, dx = du, x^2 + 2x + 2 = u^2 + 1 u = x + 1 ⟹ x = u − 1 , d x = d u , x 2 + 2 x + 2 = u 2 + 1 Expand numerator: ( u − 1 ) 3 = u 3 − 3 u 2 + 3 u − 1 (u - 1)^3 = u^3 - 3u^2 + 3u - 1 ( u − 1 ) 3 = u 3 − 3 u 2 + 3 u − 1 Rewrite integral: ∫ u 3 − 3 u 2 + 3 u − 1 ( u 2 + 1 ) 2 d u \int \frac{u^3 - 3u^2 + 3u - 1}{(u^2 + 1)^2}\,du ∫ ( u 2 + 1 ) 2 u 3 − 3 u 2 + 3 u − 1 d u Split into partial fractions:∫ u 3 ( u 2 + 1 ) 2 d u = 1 2 ln ( u 2 + 1 ) + 1 2 ( u 2 + 1 ) \int \frac{u^3}{(u^2 + 1)^2}\,du = \frac{1}{2}\ln(u^2 + 1) + \frac{1}{2(u^2 + 1)} ∫ ( u 2 + 1 ) 2 u 3 d u = 2 1 ln ( u 2 + 1 ) + 2 ( u 2 + 1 ) 1 ∫ − 3 u 2 ( u 2 + 1 ) 2 d u = − 3 ( 1 2 arctan ( u ) − u 2 ( u 2 + 1 ) ) \int \frac{-3u^2}{(u^2 + 1)^2}\,du = -3\left(\frac{1}{2}\arctan(u) - \frac{u}{2(u^2 + 1)}\right) ∫ ( u 2 + 1 ) 2 − 3 u 2 d u = − 3 ( 2 1 arctan ( u ) − 2 ( u 2 + 1 ) u ) ∫ 3 u ( u 2 + 1 ) 2 d u = − 3 2 ( u 2 + 1 ) \int \frac{3u}{(u^2 + 1)^2}\,du = -\frac{3}{2(u^2 + 1)} ∫ ( u 2 + 1 ) 2 3 u d u = − 2 ( u 2 + 1 ) 3 ∫ − 1 ( u 2 + 1 ) 2 d u = − 1 2 arctan ( u ) − u 2 ( u 2 + 1 ) \int \frac{-1}{(u^2 + 1)^2}\,du = -\frac{1}{2}\arctan(u) - \frac{u}{2(u^2 + 1)} ∫ ( u 2 + 1 ) 2 − 1 d u = − 2 1 arctan ( u ) − 2 ( u 2 + 1 ) u Combine and simplify in variable u u u :1 2 ln ( u 2 + 1 ) − 3 2 arctan ( u ) − u 2 + 3 u − 1 2 ( u 2 + 1 ) + C \frac{1}{2}\ln(u^2 + 1) - \frac{3}{2}\arctan(u) - \frac{u^2 + 3u - 1}{2(u^2 + 1)} + C 2 1 ln ( u 2 + 1 ) − 2 3 arctan ( u ) − 2 ( u 2 + 1 ) u 2 + 3 u − 1 + C Substitute back u = x + 1 u = x + 1 u = x + 1 1 2 ln ( x 2 + 2 x + 2 ) − 3 2 arctan ( x + 1 ) − ( x + 1 ) 2 + 3 ( x + 1 ) − 1 2 ( x 2 + 2 x + 2 ) + C \frac{1}{2}\ln(x^2 + 2x + 2) - \frac{3}{2}\arctan(x + 1) - \frac{(x + 1)^2 + 3(x + 1) - 1}{2(x^2 + 2x + 2)} + C 2 1 ln ( x 2 + 2 x + 2 ) − 2 3 arctan ( x + 1 ) − 2 ( x 2 + 2 x + 2 ) ( x + 1 ) 2 + 3 ( x + 1 ) − 1 + C The Extreme Value Theorem and Absolute Extrema Local vs. Absolute Extrema :Local Maximum/Minimum : A point where the function value is the highest or lowest relative to immediately surrounding points.Absolute Maximum/Minimum : The overall highest or lowest output value across the function's entire domain.On a closed interval, boundaries (endpoints) matter as much as interior critical points.
Extreme Value Theorem (EVT) : If f f f is continuous on a closed interval [ a , b ] [a, b] [ a , b ] , then f f f attains both an absolute maximum and an absolute minimum on [ a , b ] [a, b] [ a , b ] .Formal Statement : There exist points c , d ∈ [ a , b ] c, d \in [a, b] c , d ∈ [ a , b ] such that f ( c ) ≤ f ( x ) ≤ f ( d ) f(c) \le f(x) \le f(d) f ( c ) ≤ f ( x ) ≤ f ( d ) for every x ∈ [ a , b ] x \in [a, b] x ∈ [ a , b ] .Necessity of Hypotheses :Non-Closed Interval : The function f ( x ) = x f(x) = x f ( x ) = x on ( 0 , 1 ) (0, 1) ( 0 , 1 ) has no absolute minimum or maximum because the endpoint boundaries 0 0 0 and 1 1 1 are excluded.Discontinuity : The piecewise function f ( x ) = x f(x) = x f ( x ) = x for 0 ≤ x < 1 0 \le x < 1 0 ≤ x < 1 and f ( 1 ) = 0 f(1) = 0 f ( 1 ) = 0 on [ 0 , 1 ] [0, 1] [ 0 , 1 ] lacks an absolute maximum because its values approach 1 1 1 without ever reaching it.The Closed Interval Method : To find absolute extrema of a continuous function f f f on [ a , b ] [a, b] [ a , b ] :Verify that f f f is continuous on [ a , b ] [a, b] [ a , b ] . Find all critical numbers of f f f in the open interval ( a , b ) (a, b) ( a , b ) where f ′ ( x ) = 0 f'(x) = 0 f ′ ( x ) = 0 or f ′ ( x ) f'(x) f ′ ( x ) does not exist. Evaluate f ( x ) f(x) f ( x ) at every critical number and at the endpoints a a a and b b b Compare all resulting values. The maximum output is the absolute maximum; the minimum output is the absolute minimum. EVT Example 1 (Polynomial) : Find absolute extrema of f ( x ) = x 3 − 3 x 2 − 9 x + 5 f(x) = x^3 - 3x^2 - 9x + 5 f ( x ) = x 3 − 3 x 2 − 9 x + 5 on [ − 2 , 5 ] [-2, 5] [ − 2 , 5 ] Compute derivative: f ′ ( x ) = 3 x 2 − 6 x − 9 = 3 ( x − 3 ) ( x + 1 ) f'(x) = 3x^2 - 6x - 9 = 3(x - 3)(x + 1) f ′ ( x ) = 3 x 2 − 6 x − 9 = 3 ( x − 3 ) ( x + 1 ) Critical numbers in ( − 2 , 5 ) (-2, 5) ( − 2 , 5 ) : x = − 1 , 3 x = -1, 3 x = − 1 , 3 Evaluate inputs:f ( − 2 ) = ( − 2 ) 3 − 3 ( − 2 ) 2 − 9 ( − 2 ) + 5 = 3 f(-2) = (-2)^3 - 3(-2)^2 - 9(-2) + 5 = 3 f ( − 2 ) = ( − 2 ) 3 − 3 ( − 2 ) 2 − 9 ( − 2 ) + 5 = 3 f ( − 1 ) = ( − 1 ) 3 − 3 ( − 1 ) 2 − 9 ( − 1 ) + 5 = 10 f(-1) = (-1)^3 - 3(-1)^2 - 9(-1) + 5 = 10 f ( − 1 ) = ( − 1 ) 3 − 3 ( − 1 ) 2 − 9 ( − 1 ) + 5 = 10 f ( 3 ) = ( 3 ) 3 − 3 ( 3 ) 2 − 9 ( 3 ) + 5 = − 22 f(3) = (3)^3 - 3(3)^2 - 9(3) + 5 = -22 f ( 3 ) = ( 3 ) 3 − 3 ( 3 ) 2 − 9 ( 3 ) + 5 = − 22 f ( 5 ) = ( 5 ) 3 − 3 ( 5 ) 2 − 9 ( 5 ) + 5 = 10 f(5) = (5)^3 - 3(5)^2 - 9(5) + 5 = 10 f ( 5 ) = ( 5 ) 3 − 3 ( 5 ) 2 − 9 ( 5 ) + 5 = 10 Conclusion : Absolute maximum value is 10 10 10 at x = − 1 x = -1 x = − 1 and x = 5 x = 5 x = 5 . Absolute minimum value is − 22 -22 − 22 at x = 3 x = 3 x = 3 .
EVT Example 2 (Trigonometric Function) : Find absolute extrema of f ( x ) = sin ( x ) + cos ( x ) f(x) = \sin(x) + \cos(x) f ( x ) = sin ( x ) + cos ( x ) on [ 0 , π ] [0, \pi] [ 0 , π ] Compute derivative: f ′ ( x ) = cos ( x ) − sin ( x ) = 0 ⟹ tan ( x ) = 1 f'(x) = \cos(x) - \sin(x) = 0 \implies \tan(x) = 1 f ′ ( x ) = cos ( x ) − sin ( x ) = 0 ⟹ tan ( x ) = 1 Critical number in [ 0 , π ] [0, \pi] [ 0 , π ] : x = π / 4 x = \pi/4 x = π /4 Evaluate inputs: f ( 0 ) = 1 f(0) = 1 f ( 0 ) = 1 , f ( π / 4 ) = 2 f(\pi/4) = \sqrt{2} f ( π /4 ) = 2 , f ( π ) = − 1 f(\pi) = -1 f ( π ) = − 1 Conclusion : Absolute maximum is 2 \sqrt{2} 2 at x = π / 4 x = \pi/4 x = π /4 . Absolute minimum is − 1 -1 − 1 at x = π x = \pi x = π .EVT Example 3 (Radical Function) : Find absolute extrema of f ( x ) = x ( 4 − x ) f(x) = \sqrt{x}(4 - x) f ( x ) = x ( 4 − x ) on [ 0 , 4 ] [0, 4] [ 0 , 4 ] Compute derivative for x > 0 x > 0 x > 0 : f ′ ( x ) = 1 2 x ( 4 − x ) − x = 4 − 3 x 2 x f'(x) = \frac{1}{2\sqrt{x}}(4 - x) - \sqrt{x} = \frac{4 - 3x}{2\sqrt{x}} f ′ ( x ) = 2 x 1 ( 4 − x ) − x = 2 x 4 − 3 x Critical numbers: x = 4 / 3 x = 4/3 x = 4/3 (where f ′ = 0 f' = 0 f ′ = 0 ) and x = 0 x = 0 x = 0 (endpoint where f ′ f' f ′ is undefined) Evaluate inputs: f ( 0 ) = 0 f(0) = 0 f ( 0 ) = 0 , f ( 4 / 3 ) = 4 / 3 ( 4 − 4 / 3 ) = 16 3 3 f(4/3) = \sqrt{4/3}(4 - 4/3) = \frac{16}{3\sqrt{3}} f ( 4/3 ) = 4/3 ( 4 − 4/3 ) = 3 3 16 , f ( 4 ) = 0 f(4) = 0 f ( 4 ) = 0 Conclusion : Absolute maximum is 16 3 3 \frac{16}{3\sqrt{3}} 3 3 16 at x = 4 / 3 x = 4/3 x = 4/3 . Absolute minimum is 0 0 0 at x = 0 x = 0 x = 0 and x = 4 x = 4 x = 4 EVT Example 4 (Rational Function) : Find absolute extrema of f ( x ) = x x 2 + 1 f(x) = \frac{x}{x^2 + 1} f ( x ) = x 2 + 1 x on [ − 2 , 2 ] [-2, 2] [ − 2 , 2 ] Compute derivative: f ′ ( x ) = ( x 2 + 1 ) − 2 x 2 ( x 2 + 1 ) 2 = 1 − x 2 ( x 2 + 1 ) 2 f'(x) = \frac{(x^2 + 1) - 2x^2}{(x^2 + 1)^2} = \frac{1 - x^2}{(x^2 + 1)^2} f ′ ( x ) = ( x 2 + 1 ) 2 ( x 2 + 1 ) − 2 x 2 = ( x 2 + 1 ) 2 1 − x 2 Critical numbers: x = ± 1 x = \pm 1 x = ± 1 Evaluate inputs: f ( − 2 ) = − 2 / 5 f(-2) = -2/5 f ( − 2 ) = − 2/5 , f ( − 1 ) = − 1 / 2 f(-1) = -1/2 f ( − 1 ) = − 1/2 , f ( 1 ) = 1 / 2 f(1) = 1/2 f ( 1 ) = 1/2 , f ( 2 ) = 2 / 5 f(2) = 2/5 f ( 2 ) = 2/5 Conclusion : Absolute maximum is 1 / 2 1/2 1/2 at x = 1 x = 1 x = 1 . Absolute minimum is − 1 / 2 -1/2 − 1/2 at x = − 1 x = -1 x = − 1 .EVT Example 5 (Exponential Function) : Find absolute extrema of f ( x ) = x e − x f(x) = xe^{-x} f ( x ) = x e − x on [ 0 , 4 ] [0, 4] [ 0 , 4 ] Compute derivative: f ′ ( x ) = e − x − x e − x = e − x ( 1 − x ) f'(x) = e^{-x} - xe^{-x} = e^{-x}(1 - x) f ′ ( x ) = e − x − x e − x = e − x ( 1 − x ) Critical number: x = 1 x = 1 x = 1 Evaluate inputs: f ( 0 ) = 0 f(0) = 0 f ( 0 ) = 0 , f ( 1 ) = 1 / e f(1) = 1/e f ( 1 ) = 1/ e , f ( 4 ) = 4 / e 4 f(4) = 4/e^4 f ( 4 ) = 4/ e 4 Conclusion : Absolute maximum is 1 / e 1/e 1/ e at x = 1 x = 1 x = 1 . Absolute minimum is 0 0 0 at x = 0 x = 0 x = 0 EVT Example 6 (Logarithmic Function) : Find absolute extrema of f ( x ) = ln ( x ) − x f(x) = \ln(x) - x f ( x ) = ln ( x ) − x on [ 1 / 2 , 4 ] [1/2, 4] [ 1/2 , 4 ] Compute derivative: f ′ ( x ) = 1 x − 1 = 1 − x x f'(x) = \frac{1}{x} - 1 = \frac{1 - x}{x} f ′ ( x ) = x 1 − 1 = x 1 − x Critical number: x = 1 x = 1 x = 1 Evaluate inputs: f ( 1 / 2 ) = − ln ( 2 ) − 1 / 2 ≈ − 1.193 f(1/2) = -\ln(2) - 1/2 \approx -1.193 f ( 1/2 ) = − ln ( 2 ) − 1/2 ≈ − 1.193 , f ( 1 ) = − 1 f(1) = -1 f ( 1 ) = − 1 , f ( 4 ) = ln ( 4 ) − 4 ≈ − 2.614 f(4) = \ln(4) - 4 \approx -2.614 f ( 4 ) = ln ( 4 ) − 4 ≈ − 2.614 Conclusion : Absolute maximum is − 1 -1 − 1 at x = 1 x = 1 x = 1 . Absolute minimum is ln ( 4 ) − 4 \ln(4) - 4 ln ( 4 ) − 4 at x = 4 x = 4 x = 4 Logarithmic Differentiation and Derivative Sign Analysis Scope of Application : Logarithmic differentiation is indicated for functions involving complex products, multi-term quotients, fractional exponents, and variable powers (y = u ( x ) v ( x ) y = u(x)^{v(x)} y = u ( x ) v ( x ) ).Standard Procedure :Take the natural logarithm of both sides: ln ( y ) = ln ( f ( x ) ) \ln(y) = \ln(f(x)) ln ( y ) = ln ( f ( x )) Simplify the right side using logarithm expansion rules: ln ( A B ) = ln ( A ) + ln ( B ) \ln(AB) = \ln(A) + \ln(B) ln ( A B ) = ln ( A ) + ln ( B ) , ln ( A / B ) = ln ( A ) − ln ( B ) \ln(A/B) = \ln(A) - \ln(B) ln ( A / B ) = ln ( A ) − ln ( B ) , ln ( A r ) = r ln ( A ) \ln(A^r) = r\ln(A) ln ( A r ) = r ln ( A ) . Differentiate implicitly with respect to x x x : y ′ y = d d x [ ln ( f ( x ) ) ] \frac{y'}{y} = \frac{d}{dx}[\ln(f(x))] y y ′ = d x d [ ln ( f ( x ))] Solve for y ′ y' y ′ : y ′ = y ⋅ d d x [ ln ( f ( x ) ) ] y' = y \cdot \frac{d}{dx}[\ln(f(x))] y ′ = y ⋅ d x d [ ln ( f ( x ))] Substitute the original expression for y y y Logarithmic Differentiation Examples :Variable Power y = x x y = x^x y = x x (x > 0 x > 0 x > 0 ) :ln ( y ) = x ln ( x ) ⟹ y ′ y = ln ( x ) + 1 ⟹ y ′ = x x ( ln ( x ) + 1 ) \ln(y) = x\ln(x) \implies \frac{y'}{y} = \ln(x) + 1 \implies y' = x^x(\ln(x) + 1) ln ( y ) = x ln ( x ) ⟹ y y ′ = ln ( x ) + 1 ⟹ y ′ = x x ( ln ( x ) + 1 ) Trigonometric Power y = ( sin ( x ) ) x y = (\sin(x))^x y = ( sin ( x ) ) x (sin ( x ) > 0 \sin(x) > 0 sin ( x ) > 0 ) :ln ( y ) = x ln ( sin ( x ) ) ⟹ y ′ y = ln ( sin ( x ) ) + x cot ( x ) ⟹ y ′ = ( sin ( x ) ) x [ ln ( sin ( x ) ) + x cot ( x ) ] \ln(y) = x\ln(\sin(x)) \implies \frac{y'}{y} = \ln(\sin(x)) + x\cot(x) \implies y' = (\sin(x))^x [\ln(\sin(x)) + x\cot(x)] ln ( y ) = x ln ( sin ( x )) ⟹ y y ′ = ln ( sin ( x )) + x cot ( x ) ⟹ y ′ = ( sin ( x ) ) x [ ln ( sin ( x )) + x cot ( x )] Product of Powers y = ( x 2 + 1 ) 5 ( 3 x − 1 ) 4 x + 2 y = (x^2 + 1)^5(3x - 1)^4\sqrt{x + 2} y = ( x 2 + 1 ) 5 ( 3 x − 1 ) 4 x + 2 :ln ( y ) = 5 ln ( x 2 + 1 ) + 4 ln ( 3 x − 1 ) + 1 2 ln ( x + 2 ) \ln(y) = 5\ln(x^2 + 1) + 4\ln(3x - 1) + \frac{1}{2}\ln(x + 2) ln ( y ) = 5 ln ( x 2 + 1 ) + 4 ln ( 3 x − 1 ) + 2 1 ln ( x + 2 ) y ′ y = 10 x x 2 + 1 + 12 3 x − 1 + 1 2 ( x + 2 ) \frac{y'}{y} = \frac{10x}{x^2 + 1} + \frac{12}{3x - 1} + \frac{1}{2(x + 2)} y y ′ = x 2 + 1 10 x + 3 x − 1 12 + 2 ( x + 2 ) 1 y ′ = ( x 2 + 1 ) 5 ( 3 x − 1 ) 4 x + 2 [ 10 x x 2 + 1 + 12 3 x − 1 + 1 2 ( x + 2 ) ] y' = (x^2 + 1)^5(3x - 1)^4\sqrt{x + 2} \left[\frac{10x}{x^2 + 1} + \frac{12}{3x - 1} + \frac{1}{2(x + 2)}\right] y ′ = ( x 2 + 1 ) 5 ( 3 x − 1 ) 4 x + 2 [ x 2 + 1 10 x + 3 x − 1 12 + 2 ( x + 2 ) 1 ] Complex Quotient y = x 3 x 2 + 4 ( 5 x − 2 ) 7 ( x + 1 ) 2 y = \frac{x^3\sqrt{x^2 + 4}}{(5x - 2)^7(x + 1)^2} y = ( 5 x − 2 ) 7 ( x + 1 ) 2 x 3 x 2 + 4 :ln ( y ) = 3 ln ( x ) + 1 2 ln ( x 2 + 4 ) − 7 ln ( 5 x − 2 ) − 2 ln ( x + 1 ) \ln(y) = 3\ln(x) + \frac{1}{2}\ln(x^2 + 4) - 7\ln(5x - 2) - 2\ln(x + 1) ln ( y ) = 3 ln ( x ) + 2 1 ln ( x 2 + 4 ) − 7 ln ( 5 x − 2 ) − 2 ln ( x + 1 ) y ′ y = 3 x + x x 2 + 4 − 35 5 x − 2 − 2 x + 1 \frac{y'}{y} = \frac{3}{x} + \frac{x}{x^2 + 4} - \frac{35}{5x - 2} - \frac{2}{x + 1} y y ′ = x 3 + x 2 + 4 x − 5 x − 2 35 − x + 1 2 y ′ = y [ 3 x + x x 2 + 4 − 35 5 x − 2 − 2 x + 1 ] y' = y \left[\frac{3}{x} + \frac{x}{x^2 + 4} - \frac{35}{5x - 2} - \frac{2}{x + 1}\right] y ′ = y [ x 3 + x 2 + 4 x − 5 x − 2 35 − x + 1 2 ] Variable Radical Power y = ( ln ( x ) ) x y = (\ln(x))^{\sqrt{x}} y = ( ln ( x ) ) x (x > 1 x > 1 x > 1 ) :ln ( y ) = x ln ( ln ( x ) ) \ln(y) = \sqrt{x}\ln(\ln(x)) ln ( y ) = x ln ( ln ( x )) y ′ y = 1 2 x ln ( ln ( x ) ) + x ⋅ 1 x ln ( x ) = ln ( ln ( x ) ) 2 x + 1 x ln ( x ) \frac{y'}{y} = \frac{1}{2\sqrt{x}}\ln(\ln(x)) + \sqrt{x}\cdot\frac{1}{x\ln(x)} = \frac{\ln(\ln(x))}{2\sqrt{x}} + \frac{1}{\sqrt{x}\ln(x)} y y ′ = 2 x 1 ln ( ln ( x )) + x ⋅ x l n ( x ) 1 = 2 x l n ( l n ( x )) + x l n ( x ) 1 y ′ = ( ln ( x ) ) x [ ln ( ln ( x ) ) 2 x + 1 x ln ( x ) ] y' = (\ln(x))^{\sqrt{x}} \left[\frac{\ln(\ln(x))}{2\sqrt{x}} + \frac{1}{\sqrt{x}\ln(x)}\right] y ′ = ( ln ( x ) ) x [ 2 x l n ( l n ( x )) + x l n ( x ) 1 ] Exponential Base Power y = ( x 2 + 1 ) sin ( x ) y = (x^2 + 1)^{\sin(x)} y = ( x 2 + 1 ) s i n ( x ) :ln ( y ) = sin ( x ) ln ( x 2 + 1 ) \ln(y) = \sin(x)\ln(x^2 + 1) ln ( y ) = sin ( x ) ln ( x 2 + 1 ) y ′ y = cos ( x ) ln ( x 2 + 1 ) + sin ( x ) ⋅ 2 x x 2 + 1 \frac{y'}{y} = \cos(x)\ln(x^2 + 1) + \sin(x)\cdot\frac{2x}{x^2 + 1} y y ′ = cos ( x ) ln ( x 2 + 1 ) + sin ( x ) ⋅ x 2 + 1 2 x y ′ = ( x 2 + 1 ) sin ( x ) [ cos ( x ) ln ( x 2 + 1 ) + 2 x sin ( x ) x 2 + 1 ] y' = (x^2 + 1)^{\sin(x)} \left[\cos(x)\ln(x^2 + 1) + \frac{2x\sin(x)}{x^2 + 1}\right] y ′ = ( x 2 + 1 ) s i n ( x ) [ cos ( x ) ln ( x 2 + 1 ) + x 2 + 1 2 x s i n ( x ) ] Monotonicity Analysis via f ′ f \frac{f'}{f} f f ′ : If f ( x ) > 0 f(x) > 0 f ( x ) > 0 , then f ′ ( x ) = f ( x ) d d x [ ln ( f ( x ) ) ] f'(x) = f(x)\frac{d}{dx}[\ln(f(x))] f ′ ( x ) = f ( x ) d x d [ ln ( f ( x ))] . Since f ( x ) > 0 f(x) > 0 f ( x ) > 0 , the sign of f ′ ( x ) f'(x) f ′ ( x ) is completely determined by the sign of f ′ ( x ) f ( x ) = d d x [ ln ( f ( x ) ) ] \frac{f'(x)}{f(x)} = \frac{d}{dx}[\ln(f(x))] f ( x ) f ′ ( x ) = d x d [ ln ( f ( x ))] .Example 1 : f ( x ) = x x 2 + 1 f(x) = \frac{x}{x^2 + 1} f ( x ) = x 2 + 1 x for x > 0 x > 0 x > 0 ln ( f ) = ln ( x ) − ln ( x 2 + 1 ) ⟹ f ′ f = 1 x − 2 x x 2 + 1 = 1 − x 2 x ( x 2 + 1 ) \ln(f) = \ln(x) - \ln(x^2 + 1) \implies \frac{f'}{f} = \frac{1}{x} - \frac{2x}{x^2 + 1} = \frac{1 - x^2}{x(x^2 + 1)} ln ( f ) = ln ( x ) − ln ( x 2 + 1 ) ⟹ f f ′ = x 1 − x 2 + 1 2 x = x ( x 2 + 1 ) 1 − x 2 The sign depends on 1 − x 2 1 - x^2 1 − x 2 . Thus, f f f is increasing on ( 0 , 1 ) (0, 1) ( 0 , 1 ) and decreasing on ( 1 , ∞ ) (1, \infty) ( 1 , ∞ ) . Example 2 : f ( x ) = x 2 e − x f(x) = x^2 e^{-x} f ( x ) = x 2 e − x for x > 0 x > 0 x > 0 ln ( f ) = 2 ln ( x ) − x ⟹ f ′ f = 2 x − 1 = 2 − x x \ln(f) = 2\ln(x) - x \implies \frac{f'}{f} = \frac{2}{x} - 1 = \frac{2 - x}{x} ln ( f ) = 2 ln ( x ) − x ⟹ f f ′ = x 2 − 1 = x 2 − x f f f is increasing on ( 0 , 2 ) (0, 2) ( 0 , 2 ) and decreasing on ( 2 , ∞ ) (2, \infty) ( 2 , ∞ ) .Example 3 : f ( x ) = x 3 ( x + 1 ) 4 f(x) = \frac{x^3}{(x + 1)^4} f ( x ) = ( x + 1 ) 4 x 3 for x > 0 x > 0 x > 0 ln ( f ) = 3 ln ( x ) − 4 ln ( x + 1 ) ⟹ f ′ f = 3 x − 4 x + 1 = 3 − x x ( x + 1 ) \ln(f) = 3\ln(x) - 4\ln(x + 1) \implies \frac{f'}{f} = \frac{3}{x} - \frac{4}{x + 1} = \frac{3 - x}{x(x + 1)} ln ( f ) = 3 ln ( x ) − 4 ln ( x + 1 ) ⟹ f f ′ = x 3 − x + 1 4 = x ( x + 1 ) 3 − x f f f is increasing on ( 0 , 3 ) (0, 3) ( 0 , 3 ) and decreasing on ( 3 , ∞ ) (3, \infty) ( 3 , ∞ ) .Example 4 : f ( x ) = x a ( 1 − x ) b f(x) = x^a(1 - x)^b f ( x ) = x a ( 1 − x ) b for 0 < x < 1 0 < x < 1 0 < x < 1 (a , b > 0 a, b > 0 a , b > 0 )ln ( f ) = a ln ( x ) + b ln ( 1 − x ) ⟹ f ′ f = a x − b 1 − x = a − ( a + b ) x x ( 1 − x ) \ln(f) = a\ln(x) + b\ln(1 - x) \implies \frac{f'}{f} = \frac{a}{x} - \frac{b}{1 - x} = \frac{a - (a + b)x}{x(1 - x)} ln ( f ) = a ln ( x ) + b ln ( 1 − x ) ⟹ f f ′ = x a − 1 − x b = x ( 1 − x ) a − ( a + b ) x f f f is increasing on ( 0 , a a + b ) \left(0, \frac{a}{a + b}\right) ( 0 , a + b a ) and decreasing on ( a a + b , 1 ) \left(\frac{a}{a + b}, 1\right) ( a + b a , 1 ) .Intermediate Value Theorem (IVT) : If f f f is continuous on [ a , b ] [a, b] [ a , b ] and N N N is any real number between f ( a ) f(a) f ( a ) and f ( b ) f(b) f ( b ) , then there exists at least one value c ∈ ( a , b ) c \in (a, b) c ∈ ( a , b ) such that f(c) = N$.\n * *Root-Finding Variant*: If fi s c o n t i n u o u s o n is continuous on i sco n t in u o u so n [a, b]a n d and an d f(a)f(b) < 0( o p p o s i t e s i g n s ) , t h e r e e x i s t s (opposite signs), there exists ( o pp os i t es i g n s ) , t h er ee x i s t s c \in (a, b)s u c h t h a t such that s u c h t ha t f(c) = 0$.IVT Application Examples :Polynomial Root : Show f ( x ) = x 3 + x − 1 f(x) = x^3 + x - 1 f ( x ) = x 3 + x − 1 has a root in ( 0 , 1 ) (0, 1) ( 0 , 1 ) .f ( 0 ) = − 1 < 0 f(0) = -1 < 0 f ( 0 ) = − 1 < 0 and f ( 1 ) = 1 > 0 f(1) = 1 > 0 f ( 1 ) = 1 > 0 . By IVT, a root c ∈ ( 0 , 1 ) c \in (0, 1) c ∈ ( 0 , 1 ) exists.Trigonometric Root : Show f ( x ) = cos ( x ) − x f(x) = \cos(x) - x f ( x ) = cos ( x ) − x has a root in ( 0 , 1 ) (0, 1) ( 0 , 1 ) .f ( 0 ) = 1 > 0 f(0) = 1 > 0 f ( 0 ) = 1 > 0 and f ( 1 ) = cos ( 1 ) − 1 < 0 f(1) = \cos(1) - 1 < 0 f ( 1 ) = cos ( 1 ) − 1 < 0 . By IVT, cos ( c ) = c \cos(c) = c cos ( c ) = c for some c ∈ ( 0 , 1 ) c \in (0, 1) c ∈ ( 0 , 1 ) .Logarithmic Equation : Show ln ( x ) = x − 2 \ln(x) = x - 2 ln ( x ) = x − 2 has a solution in ( 1 , 4 ) (1, 4) ( 1 , 4 ) .Define f ( x ) = ln ( x ) − x + 2 f(x) = \ln(x) - x + 2 f ( x ) = ln ( x ) − x + 2 . f ( 1 ) = 1 > 0 f(1) = 1 > 0 f ( 1 ) = 1 > 0 and f ( 4 ) = ln ( 4 ) − 2 ≈ − 0.614 < 0 f(4) = \ln(4) - 2 \approx -0.614 < 0 f ( 4 ) = ln ( 4 ) − 2 ≈ − 0.614 < 0 . IVT guarantees a root. Sequential Sign Testing : For f ( x ) = x 3 − 2 x − 5 f(x) = x^3 - 2x - 5 f ( x ) = x 3 − 2 x − 5 :f ( 2 ) = − 1 < 0 f(2) = -1 < 0 f ( 2 ) = − 1 < 0 and f ( 3 ) = 16 > 0 ⟹ f(3) = 16 > 0 \implies f ( 3 ) = 16 > 0 ⟹ root lies in ( 2 , 3 ) (2, 3) ( 2 , 3 ) .Midpoint x = 2.5 x = 2.5 x = 2.5 : f ( 2.5 ) = 5.625 > 0 ⟹ f(2.5) = 5.625 > 0 \implies f ( 2.5 ) = 5.625 > 0 ⟹ root lies in ( 2 , 2.5 ) (2, 2.5) ( 2 , 2.5 ) . Midpoint x = 2.25 x = 2.25 x = 2.25 : f ( 2.25 ) = 1.890625 > 0 ⟹ f(2.25) = 1.890625 > 0 \implies f ( 2.25 ) = 1.890625 > 0 ⟹ root lies in ( 2 , 2.25 ) (2, 2.25) ( 2 , 2.25 ) . Bisection Method Procedure :Start with an interval [ a , b ] [a, b] [ a , b ] where f ( a ) f ( b ) < 0 f(a)f(b) < 0 f ( a ) f ( b ) < 0 Calculate the midpoint m = a + b 2 m = \frac{a + b}{2} m = 2 a + b If f ( m ) = 0 f(m) = 0 f ( m ) = 0 , m m m is the exact root. If f ( a ) f ( m ) < 0 f(a)f(m) < 0 f ( a ) f ( m ) < 0 , the root lies in [ a , m ] [a, m] [ a , m ] . Set new interval to [ a , m ] [a, m] [ a , m ] . If f ( m ) f ( b ) < 0 f(m)f(b) < 0 f ( m ) f ( b ) < 0 , the root lies in [ m , b ] [m, b] [ m , b ] . Set new interval to [ m , b ] [m, b] [ m , b ] . Repeat sequentially. Each step halves the interval length. Bisection Error Analysis :After n n n bisection steps, the interval length is b − a 2 n \frac{b - a}{2^n} 2 n b − a . The maximum error when estimating the root by the midpoint of the final interval is b − a 2 n + 1 \frac{b - a}{2^{n + 1}} 2 n + 1 b − a . Step Calculation Example : To guarantee interval length below ε = 0.001 \varepsilon = 0.001 ε = 0.001 starting from [ 2 , 3 ] [2, 3] [ 2 , 3 ] :1 2 n < 0.001 ⟹ 2 n > 1000 \frac{1}{2^n} < 0.001 \implies 2^n > 1000 2 n 1 < 0.001 ⟹ 2 n > 1000 . Since 2 10 = 1024 2^{10} = 1024 2 10 = 1024 , 10 10 10 bisection steps are required.Bisection Worked Example 1 (x 3 + x − 1 = 0 x^3 + x - 1 = 0 x 3 + x − 1 = 0 on [ 0 , 1 ] [0, 1] [ 0 , 1 ] ) :Initial: f ( 0 ) = − 1 f(0) = -1 f ( 0 ) = − 1 , f ( 1 ) = 1 f(1) = 1 f ( 1 ) = 1 Step 1: m 1 = 0.5 m_1 = 0.5 m 1 = 0.5 , f ( 0.5 ) = − 0.375 < 0 ⟹ f(0.5) = -0.375 < 0 \implies f ( 0.5 ) = − 0.375 < 0 ⟹ interval [ 0.5 , 1 ] [0.5, 1] [ 0.5 , 1 ] Step 2: m 2 = 0.75 m_2 = 0.75 m 2 = 0.75 , f ( 0.75 ) = 0.171875 > 0 ⟹ f(0.75) = 0.171875 > 0 \implies f ( 0.75 ) = 0.171875 > 0 ⟹ interval [ 0.5 , 0.75 ] [0.5, 0.75] [ 0.5 , 0.75 ] Step 3: m 3 = 0.625 m_3 = 0.625 m 3 = 0.625 , f ( 0.625 ) = − 0.130859 < 0 ⟹ f(0.625) = -0.130859 < 0 \implies f ( 0.625 ) = − 0.130859 < 0 ⟹ interval [ 0.625 , 0.75 ] [0.625, 0.75] [ 0.625 , 0.75 ] Step 4: m 4 = 0.6875 m_4 = 0.6875 m 4 = 0.6875 , f ( 0.6875 ) ≈ 0.01245 > 0 ⟹ f(0.6875) \approx 0.01245 > 0 \implies f ( 0.6875 ) ≈ 0.01245 > 0 ⟹ interval [ 0.625 , 0.6875 ] [0.625, 0.6875] [ 0.625 , 0.6875 ] Midpoint estimate: x ≈ 0.625 + 0.6875 2 = 0.65625 x \approx \frac{0.625 + 0.6875}{2} = 0.65625 x ≈ 2 0.625 + 0.6875 = 0.65625 Bisection Worked Example 2 (cos ( x ) = x \cos(x) = x cos ( x ) = x on [ 0 , 1 ] [0, 1] [ 0 , 1 ] ) :Initial: f ( 0 ) = 1 > 0 f(0) = 1 > 0 f ( 0 ) = 1 > 0 , f ( 1 ) = cos ( 1 ) − 1 < 0 f(1) = \cos(1) - 1 < 0 f ( 1 ) = cos ( 1 ) − 1 < 0 Step 1: m 1 = 0.5 m_1 = 0.5 m 1 = 0.5 , f ( 0.5 ) = cos ( 0.5 ) − 0.5 ≈ 0.3776 > 0 ⟹ f(0.5) = \cos(0.5) - 0.5 \approx 0.3776 > 0 \implies f ( 0.5 ) = cos ( 0.5 ) − 0.5 ≈ 0.3776 > 0 ⟹ interval [ 0.5 , 1 ] [0.5, 1] [ 0.5 , 1 ] Step 2: m 2 = 0.75 m_2 = 0.75 m 2 = 0.75 , f ( 0.75 ) = cos ( 0.75 ) − 0.75 ≈ − 0.0183 < 0 ⟹ f(0.75) = \cos(0.75) - 0.75 \approx -0.0183 < 0 \implies f ( 0.75 ) = cos ( 0.75 ) − 0.75 ≈ − 0.0183 < 0 ⟹ interval [ 0.5 , 0.75 ] [0.5, 0.75] [ 0.5 , 0.75 ] Accumulation Functions and the Fundamental Theorem of Calculus Definite Integrals vs. Antiderivatives :An indefinite integral is a family of functions F ( x ) + C F(x) + C F ( x ) + C . A definite integral ∫ a b f ( x ) d x \int_a^b f(x)\,dx ∫ a b f ( x ) d x is a numerical value representing net signed area. The Accumulation Function : Fix a a a and define A ( x ) = ∫ a x f ( t ) d t A(x) = \int_a^x f(t)\,dt A ( x ) = ∫ a x f ( t ) d t
Difference Quotient Derivation :A ( x + h ) − A ( x ) = ∫ x x + h f ( t ) d t A(x + h) - A(x) = \int_x^{x + h} f(t)\,dt A ( x + h ) − A ( x ) = ∫ x x + h f ( t ) d t For small h h h , the strip area is approximated by f ( x ) h f(x)h f ( x ) h , giving A ( x + h ) − A ( x ) h ≈ f ( x ) \frac{A(x + h) - A(x)}{h} \approx f(x) h A ( x + h ) − A ( x ) ≈ f ( x ) By the Mean Value Theorem for integrals, ∫ x x + h f ( t ) d t = f ( c h ) h \int_x^{x + h} f(t)\,dt = f(c_h)h ∫ x x + h f ( t ) d t = f ( c h ) h for some c h c_h c h between x x x and x + h x + h x + h . Divide by h h h : A ( x + h ) − A ( x ) h = f ( c h ) \frac{A(x + h) - A(x)}{h} = f(c_h) h A ( x + h ) − A ( x ) = f ( c h ) . Taking $h \to 0f o r c e s forces f or ces c_h \to x, s o c o n t i n u i t y g i v e s , so continuity gives , soco n t in u i t y g i v es A'(x) = f(x).\n* **Fundamental Theorem of Calculus, Part I (FTC I)**:\n * If fi s c o n t i n u o u s o n is continuous on i sco n t in u o u so n [a, b]a n d and an d A(x) = \int_a^x f(t)\,dt, t h e n , then , t h e n A'(x) = f(x).\n * *Core Principle*: Differentiation reverses integration accumulation.\n* **Fundamental Theorem of Calculus, Part II (FTC II)**:\n * If fi s c o n t i n u o u s o n is continuous on i sco n t in u o u so n [a, b]a n d and an d Fi s a n y a n t i d e r i v a t i v e o f is any antiderivative of i s an y an t i d er i v a t i v eo f f( ( ( F' = f), then:\n * \int_a^b f(x)\,dx = F(b) - F(a)\n * *Proof*: Let A(x) = \int_a^x f(t)\,dt. T h e n . Then . T h e n A' = f = F', m e a n i n g , meaning , m e anin g A(x) - F(x) = C. S i n c e . Since . S in ce A(a) = 0, , , C = -F(a). T h e r e f o r e . Therefore . T h er e f or e A(b) = F(b) - F(a).\n * *Example*: \int_0^2 (3x^2 + 1)\,dx = [x^3 + x]0^2 = (2^3 + 2) - (0) = 10\n\n# Differentiation of Integrals with Variable Limits\n\n* **Variable Upper Limit Rule**:\n * If y = \int_a^{g(x)} f(t)\,dt, l e t , let , l e t u = g(x). By FTC I and Chain Rule:\n * y' = f(g(x))g'(x)\n * *Example 1*: \frac{d}{dx}\left[\int_2^{x^3} \sin(t^2)\,dt\right] = \sin((x^3)^2)\cdot(3x^2) = 3x^2\sin(x^6)\n * *Example 2*: \frac{d}{dx}\left[\int_1^{\sqrt{1 + x^2}} e^{-t^2}\,dt\right] = e^{-(\sqrt{1 + x^2})^2}\cdot\frac{d}{dx}\left(\sqrt{1 + x^2}\right) = \frac{xe^{-(1 + x^2)}}{\sqrt{1 + x^2}}\n* **Both Limits Variable Rule**:\n * If y = \int {u(x)}^{v(x)} f(t)\,dt, then:\n * y' = f(v(x))v'(x) - f(u(x))u'(x)\n * *Example 3*: \frac{d}{dx}\left[\int_{x^2}^{2 + \sin(x)} \ln(1 + t^4)\,dt\right] = \cos(x)\ln(1 + (2 + \sin(x))^4) - 2x\ln(1 + x^8)\n * *Practice*: \frac{d}{dx}\left[\int_{\cos(x)}^{x^2 + 1} \frac{dt}{1 + t^4}\right] = \frac{2x}{1 + (x^2 + 1)^4} + \frac{\sin(x)}{1 + \cos^4(x)}\n* **Chain-Rule Warning**: For F(x) = \int_1^{x^2} e^{-t^2}\,dt, e v a l u a t i n g d i r e c t l y a s , evaluating directly as , e v a l u a t in g d i r ec tl y a s e^{-x^2}i s i n c o r r e c t . T h e u p p e r l i m i t is incorrect. The upper limit i s in cor r ec t . T h e u pp er l imi t x^2r e q u i r e s m u l t i p l y i n g b y i t s d e r i v a t i v e requires multiplying by its derivative r e q u i r es m u l t i pl y in g b y i t s d er i v a t i v e 2x, y i e l d i n g , yielding , y i e l d in g F'(x) = 2xe^{-x^4}.\n\n# Riemann Sums and Definite Integrals\n\n* **Partition Construction**: Divide [a, b]i n t o into in t o ns u b i n t e r v a l s o f e q u a l w i d t h subintervals of equal width s u bin t er v a l so f e q u a l w i d t h \Delta x = \frac{b - a}{n}, w i t h g r i d p o i n t s , with grid points , w i t h g r i d p o in t s x_k = a + k\Delta x.\n* **Riemann Sum Definition**: On each subinterval [x_{k-1}, x_k], p i c k a s a m p l e p o i n t , pick a sample point , p i c k a s am pl e p o in t x_k^. The corresponding sum is:\n * S_n = \sum_{k=1}^n f(x_k^ )\Delta x\n* **Definite Integral as a Limit**: For continuous f:\n * \int_a^b f(x)\,dx = \lim_{n \to \infty} \sum_{k=1}^n f(x_k^)\Delta x\n* **Endpoint Choices**:\n * *Left Endpoints* (x_k^ = x_{k-1} = a + (k - 1)\Delta x) : ): ) : L_n = \sum_{k=1}^n f(a + (k - 1)\Delta x)\Delta x\n * *Right Endpoints* (x_k^* = x_k = a + k\Delta x) : ): ) : R_n = \sum_{k=1}^n f(a + k\Delta x)\Delta x\n * For an increasing positive function, L_n \le \int_a^b f(x)\,dx \le R_n\n* **Comprehensive Quadratic Example (f(x) = x^2 + 1o n on o n [0, 2])**:\n * Width: \Delta x = \frac{2}{n}, g r i d p o i n t s , grid points , g r i d p o in t s x_k = \frac{2k}{n}\n * *Four Subintervals (n = 4, \Delta x = 1/2) ∗ : E n d p o i n t s a r e )*: Endpoints are ) ∗ : E n d p o in t s a r e 0, 1/2, 1, 3/2, 2\n * L_4 = \frac{1}{2}\left(f(0) + f(1/2) + f(1) + f(3/2)\right) = \frac{1}{2}\left(1 + \frac{5}{4} + 2 + \frac{13}{4}\right) = \frac{15}{4} = 3.75\n * R_4 = \frac{1}{2}\left(f(1/2) + f(1) + f(3/2) + f(2)\right) = \frac{1}{2}\left(\frac{5}{4} + 2 + \frac{13}{4} + 5\right) = \frac{23}{4} = 5.75\n * Area bound: 3.75 < \int_0^2 (x^2 + 1)\,dx < 5.75\n * *General Left Sum L_n*:\n * L_n = \sum_{k=1}^n \left[\left(\frac{2(k - 1)}{n}\right)^2 + 1\right]\frac{2}{n} = \frac{8}{n^3}\sum_{k=1}^n (k - 1)^2 + 2\n * Using \sum_{j=0}^{n-1} j^2 = \frac{(n - 1)n(2n - 1)}{6}:\n * L_n = 2 + \frac{4(n - 1)(2n - 1)}{3n^2} = 2 + \frac{8}{3} - \frac{4}{n} + \frac{4}{3n^2} \implies \lim_{n \to \infty} L_n = \frac{14}{3}\n * *General Right Sum R_n*:\n * R_n = \sum_{k=1}^n \left[\left(\frac{2k}{n}\right)^2 + 1\right]\frac{2}{n} = \frac{8}{n^3}\sum_{k=1}^n k^2 + 2\n * Using \sum_{k=1}^n k^2 = \frac{n(n + 1)(2n + 1)}{6}:\n * R_n = 2 + \frac{4(n + 1)(2n + 1)}{3n^2} = 2 + \frac{8}{3} + \frac{4}{n} + \frac{4}{3n^2} \implies \lim_{n \to \infty} R_n = \frac{14}{3}\n * *Approximation Gap*: R_n - L_n = \frac{8}{n}. A s . As . A s n \to \infty, the gap shrinks to zero.\n * *FTC Verification*: \int_0^2 (x^2 + 1)\,dx = \left[\frac{x^3}{3} + x\right]0^2 = \frac{8}{3} + 2 = \frac{14}{3}\n* **Recognizing Limits as Definite Integrals**:\n * Convert \lim {n \to \infty} \frac{1}{n}\sum_{k=1}^n \left(1 + \frac{k}{n}\right)^2:\n * Identify \Delta x = \frac{1}{n}a n d and an d x_k = 1 + \frac{k}{n}o n i n t e r v a l on interval o nin t er v a l [1, 2]\n * Limit represents \int_1^2 x^2\,dx\n* **Converting Integrals to Limit Sums**:\n * Write \int_2^5 (x^2 + 3)\,dx as a right-endpoint limit:\n * \Delta x = \frac{3}{n}, , , x_k = 2 + \frac{3k}{n} \implies \lim_{n \to \infty} \sum_{k=1}^n \left[\left(2 + \frac{3k}{n}\right)^2 + 3\right]\frac{3}{n}\n\n# Implicit Differentiation and Geometric Applications\n\n* **Implicit Functions**: Equations such as x^2 + y^2 = 25d e f i n e define d e f in e yi m p l i c i t l y a s a f u n c t i o n o f implicitly as a function of im pl i c i tl y a s a f u n c t i o n o f x. I m p l i c i t d i f f e r e n t i a t i o n y i e l d s . Implicit differentiation yields . I m pl i c i t d i f f er e n t ia t i o n y i e l d s \frac{dy}{dx}d i r e c t l y w i t h o u t r e q u i r i n g e x p l i c i t s o l u t i o n f o r directly without requiring explicit solution for d i r ec tl y w i t h o u t r e q u i r in g e x pl i c i t so l u t i o n f or y\n* **Chain Rule Mechanics**: Treating ya s as a s y(x), d i f f e r e n t i a t i o n a p p l i e s t h e p o w e r c h a i n r u l e : , differentiation applies the power chain rule: , d i f f er e n t ia t i o na ppl i es t h e p o w er c hain r u l e : \frac{d}{dx}(y^n) = n y^{n-1} y'\n* **Implicit Differentiation Steps**:\n 1. Differentiate both sides of the equation with respect to x.\n 2. Attach y'w h e n e v e r d i f f e r e n t i a t i n g a t e r m i n v o l v i n g whenever differentiating a term involving w h e n e v er d i f f er e n t ia t in g a t er min v o l v in g y\n 3. Apply Product, Quotient, and Chain rules as necessary.\n 4. Collect all terms containing y' on one side and move remaining terms to the opposite side.\n 5. Factor out y' and solve.\n* **Implicit Differentiation Examples**:\n * *Circle Equation x^2 + y^2 = 25*:\n * 2x + 2yy' = 0 \implies y' = -\frac{x}{y}\n\n\n\n * Slope at (3, 4): : : m = -3/4\n * Tangent Line at (3, 4): : : y - 4 = -\frac{3}{4}(x - 3) \implies 3x + 4y = 25\n * *Product Term x^2 + xy + y^2 = 7*:\n * 2x + (xy' + y) + 2yy' = 0 \implies (x + 2y)y' = -(2x + y) \implies y' = -\frac{2x + y}{x + 2y}\n * Slope at (1, 2): : : m = -\frac{2(1) + 2}{1 + 2(2)} = -4/5\n * *Folium Curve x^3 + y^3 = 6xy*:\n * 3x^2 + 3y^2y' = 6y + 6xy' \implies (3y^2 - 6x)y' = 6y - 3x^2 \implies y' = \frac{2y - x^2}{y^2 - 2x}\n * Slope at (3, 3): : : y' = -1\n * *Mixed Terms x^2 y + y^3 = 10*:\n * 2xy + x^2y' + 3y^2y' = 0 \implies y' = -\frac{2xy}{x^2 + 3y^2}\n * *Trigonometric Equation \sin(y) + x^2 y = 4*:\n * \cos(y)y' + 2xy + x^2y' = 0 \implies y' = -\frac{2xy}{x^2 + \cos(y)}\n * *Exponential Equation e^{xy} + x + y = 3*:\n * e^{xy}(xy' + y) + 1 + y' = 0 \implies (x e^{xy} + 1)y' = -(y e^{xy} + 1) \implies y' = -\frac{y e^{xy} + 1}{x e^{xy} + 1}\n * *Practice Equation x^2 + 4xy + 4y^2 = 9*:\n * 2x + 4(xy' + y) + 8yy' = 0 \implies (4x + 8y)y' = -(2x + 4y) \implies y' = -\frac{x + 2y}{2x + 4y} = -1/2\n\n# Monotonicity, Concavity, and Derivative Tests\n\n* **Monotonicity (Increasing / Decreasing)**:\n * f'(x) > 0o n a n i n t e r v a l on an interval o nanin t er v a l \implies f is strictly increasing on that interval.\n * f'(x) < 0o n a n i n t e r v a l on an interval o nanin t er v a l \implies f is strictly decreasing on that interval.\n* **Critical Numbers**: A number ci n t h e d o m a i n o f in the domain of in t h e d o main o f fi s a c r i t i c a l n u m b e r i f is a critical number if i s a cr i t i c a l n u mb er i f f'(c) = 0o r or or f'(c) does not exist. Critical numbers are candidates for local extrema.\n* **First Derivative Test**: Let cb e a c r i t i c a l n u m b e r o f a c o n t i n u o u s f u n c t i o n be a critical number of a continuous function b e a cr i t i c a l n u mb er o f a co n t in u o u s f u n c t i o n f:\n * If f'c h a n g e s s i g n f r o m p o s i t i v e t o n e g a t i v e a t changes sign from positive to negative at c han g ess i g n f r o m p os i t i v e t o n e g a t i v e a t c, , , fh a s a l o c a l m a x i m u m a t has a local maximum at ha s a l oc a l ma x im u ma t c\n * If f'c h a n g e s s i g n f r o m n e g a t i v e t o p o s i t i v e a t changes sign from negative to positive at c han g ess i g n f r o mn e g a t i v e t o p os i t i v e a t c, , , fh a s a l o c a l m i n i m u m a t has a local minimum at ha s a l oc a l minim u ma t c\n * If f'r e t a i n s t h e s a m e s i g n o n b o t h s i d e s o f retains the same sign on both sides of r e t ain s t h es am es i g n o nb o t h s i d eso f c, , , fh a s n o l o c a l e x t r e m u m a t has no local extremum at ha s n o l oc a l e x t r e m u ma t c\n * *Example 1*: f(x) = x^3 - 3x \implies f'(x) = 3(x - 1)(x + 1). L o c a l m a x a t . Local max at . L oc a l ma x a t (-1, 2), l o c a l m i n a t , local min at , l oc a l mina t (1, -2).\n * *Example 2*: f(x) = x^4 - 2x^2 \implies f'(x) = 4x(x - 1)(x + 1). C r i t i c a l n u m b e r s . Critical numbers . C r i t i c a l n u mb er s x = -1, 0, 1. L o c a l m i n i m a a t . Local minima at . L oc a l minimaa t x = \pm 1, l o c a l m a x a t , local max at , l oc a l ma x a t x = 0\n * *Example 3*: f(x) = |x| \implies f'(x) = -1f o r for f or x < 0a n d and an d f'(x) = 1f o r for f or x > 0. D e r i v a t i v e d o e s n o t e x i s t a t . Derivative does not exist at . D er i v a t i v e d oes n o t e x i s t a t x = 0. S i g n c h a n g e s . Sign changes . S i g n c han g es -$ to + + + , so x = 0 x = 0 x = 0 is a local minimum. Concavity and Inflection Points :Concave Up : f ′ ′ ( x ) > 0 f''(x) > 0 f ′′ ( x ) > 0 (slopes f ′ f' f ′ are increasing). Graph lies above tangent lines.Concave Down : f ′ ′ ( x ) < 0 f''(x) < 0 f ′′ ( x ) < 0 (slopes f ′ f' f ′ are decreasing). Graph lies below tangent lines.Inflection Point : A point where the graph changes concavity and f f f is continuous.Necessary Condition : Inflection can only occur where f ′ ′ ( c ) = 0 f''(c) = 0 f ′′ ( c ) = 0 or f ′ ′ ( c ) f''(c) f ′′ ( c ) does not exist, provided f ′ ′ f'' f ′′ changes sign across c c c Example 1 : f ( x ) = x 4 − 4 x 3 ⟹ f ′ ′ ( x ) = 12 x ( x − 2 ) f(x) = x^4 - 4x^3 \implies f''(x) = 12x(x - 2) f ( x ) = x 4 − 4 x 3 ⟹ f ′′ ( x ) = 12 x ( x − 2 ) . Concave up on ( − ∞ , 0 ) ∪ ( 2 , ∞ ) (-\infty, 0) \cup (2, \infty) ( − ∞ , 0 ) ∪ ( 2 , ∞ ) , concave down on ( 0 , 2 ) (0, 2) ( 0 , 2 ) . Inflection points at x = 0 x = 0 x = 0 and x = 2 x = 2 x = 2 Example 2 : f ( x ) = x 3 ⟹ f ′ ′ ( x ) = 6 x f(x) = x^3 \implies f''(x) = 6x f ( x ) = x 3 ⟹ f ′′ ( x ) = 6 x . Inflection point at ( 0 , 0 ) (0, 0) ( 0 , 0 ) Example 3 (f ′ ′ = 0 f'' = 0 f ′′ = 0 without Inflection) : f ( x ) = x 4 ⟹ f ′ ′ ( x ) = 12 x 2 f(x) = x^4 \implies f''(x) = 12x^2 f ( x ) = x 4 ⟹ f ′′ ( x ) = 12 x 2 . Although f ′ ′ ( 0 ) = 0 f''(0) = 0 f ′′ ( 0 ) = 0 , f ′ ′ ( x ) > 0 f''(x) > 0 f ′′ ( x ) > 0 on both sides of 0 0 0 . The graph is concave up everywhere; ( 0 , 0 ) (0, 0) ( 0 , 0 ) is not an inflection point.Second Derivative Test : Suppose f ′ ( c ) = 0 f'(c) = 0 f ′ ( c ) = 0 If f ′ ′ ( c ) > 0 f''(c) > 0 f ′′ ( c ) > 0 , f f f has a local minimum at c c c If f ′ ′ ( c ) < 0 f''(c) < 0 f ′′ ( c ) < 0 , f f f has a local maximum at c c c If f ′ ′ ( c ) = 0 f''(c) = 0 f ′′ ( c ) = 0 , the test is inconclusive (use the First Derivative Test). Complete Curve Analysis and Particle Motion Curve Analysis Procedure :Determine domain and intercepts. Compute f ′ ( x ) f'(x) f ′ ( x ) and find critical numbers. Build a sign chart for f ′ ( x ) f'(x) f ′ ( x ) to establish increasing and decreasing intervals. Apply the First/Second Derivative Test to classify local extrema. Compute f ′ ′ ( x ) f''(x) f ′′ ( x ) and locate potential inflection points. Build a sign chart for f ′ ′ ( x ) f''(x) f ′′ ( x ) to establish concavity intervals. Sketch graph integrating all gathered behavior. Complete Analysis Example (f ( x ) = x 3 − 6 x 2 + 9 x f(x) = x^3 - 6x^2 + 9x f ( x ) = x 3 − 6 x 2 + 9 x ) :f ′ ( x ) = 3 x 2 − 12 x + 9 = 3 ( x − 1 ) ( x − 3 ) f'(x) = 3x^2 - 12x + 9 = 3(x - 1)(x - 3) f ′ ( x ) = 3 x 2 − 12 x + 9 = 3 ( x − 1 ) ( x − 3 ) . Critical numbers: x = 1 , 3 x = 1, 3 x = 1 , 3 Increasing on ( − ∞ , 1 ) ∪ ( 3 , ∞ ) (-\infty, 1) \cup (3, \infty) ( − ∞ , 1 ) ∪ ( 3 , ∞ ) ; Decreasing on ( 1 , 3 ) (1, 3) ( 1 , 3 ) Local maximum at ( 1 , 4 ) (1, 4) ( 1 , 4 ) ; Local minimum at ( 3 , 0 ) (3, 0) ( 3 , 0 ) f ′ ′ ( x ) = 6 x − 12 = 6 ( x − 2 ) f''(x) = 6x - 12 = 6(x - 2) f ′′ ( x ) = 6 x − 12 = 6 ( x − 2 ) Concave down on ( − ∞ , 2 ) (-\infty, 2) ( − ∞ , 2 ) ; Concave up on ( 2 , ∞ ) (2, \infty) ( 2 , ∞ ) Inflection point at ( 2 , 2 ) (2, 2) ( 2 , 2 ) Application to Motion Along a Line :Position s ( t ) s(t) s ( t ) , Velocity v ( t ) = s ′ ( t ) v(t) = s'(t) v ( t ) = s ′ ( t ) , Acceleration a ( t ) = s ′ ′ ( t ) = v ′ ( t ) a(t) = s''(t) = v'(t) a ( t ) = s ′′ ( t ) = v ′ ( t ) Example : s ( t ) = t 3 − 6 t 2 + 9 t s(t) = t^3 - 6t^2 + 9t s ( t ) = t 3 − 6 t 2 + 9 t v ( t ) = 3 ( t − 1 ) ( t − 3 ) v(t) = 3(t - 1)(t - 3) v ( t ) = 3 ( t − 1 ) ( t − 3 ) , a ( t ) = 6 ( t − 2 ) a(t) = 6(t - 2) a ( t ) = 6 ( t − 2 ) Moving forward (v ( t ) > 0 v(t) > 0 v ( t ) > 0 ) on ( 0 , 1 ) ∪ ( 3 , ∞ ) (0, 1) \cup (3, \infty) ( 0 , 1 ) ∪ ( 3 , ∞ ) Moving backward (v ( t ) < 0 v(t) < 0 v ( t ) < 0 ) on ( 1 , 3 ) (1, 3) ( 1 , 3 ) Particle changes direction at t = 1 t = 1 t = 1 and t = 3 t = 3 t = 3 Rolle's Theorem and Root Counting Connecting Local and Global Properties : Local derivative values impose strict structural bounds on overall global graph behavior.
Rolle's Theorem : Let f f f be a function satisfying:f f f is continuous on the closed interval [ a , b ] [a, b] [ a , b ] f f f is differentiable on the open interval ( a , b ) (a, b) ( a , b ) f ( a ) = f ( b ) f(a) = f(b) f ( a ) = f ( b ) Conclusion : There exists at least one value c ∈ ( a , b ) c \in (a, b) c ∈ ( a , b ) such that f ′ ( c ) = 0 f'(c) = 0 f ′ ( c ) = 0
Non-Uniqueness Warning : Rolle's Theorem guarantees the existence of at least one horizontal tangent, but there may be multiple valid values of c c c Rolle's Theorem Worked Examples :Polynomial f ( x ) = x 2 − 4 x + 3 f(x) = x^2 - 4x + 3 f ( x ) = x 2 − 4 x + 3 on [ 1 , 3 ] [1, 3] [ 1 , 3 ] :f ( 1 ) = 0 f(1) = 0 f ( 1 ) = 0 , f ( 3 ) = 0 f(3) = 0 f ( 3 ) = 0 . Polynomial is continuous and differentiable.f ′ ( x ) = 2 x − 4 = 0 ⟹ c = 2 ∈ ( 1 , 3 ) f'(x) = 2x - 4 = 0 \implies c = 2 \in (1, 3) f ′ ( x ) = 2 x − 4 = 0 ⟹ c = 2 ∈ ( 1 , 3 )
* *Trigonometric f ( x ) = sin ( x ) f(x) = \sin(x) f ( x ) = sin ( x ) on [ 0 , π ] [0, \pi] [ 0 , π ] *:
* f ( 0 ) = 0 f(0) = 0 f ( 0 ) = 0 , f ( π ) = 0 f(\pi) = 0 f ( π ) = 0
* f ′ ( x ) = cos ( x ) = 0 ⟹ c = π / 2 ∈ ( 0 , π ) f'(x) = \cos(x) = 0 \implies c = \pi/2 \in (0, \pi) f ′ ( x ) = cos ( x ) = 0 ⟹ c = π /2 ∈ ( 0 , π )
* *Rational f ( x ) = x 2 − 1 x 2 + 1 f(x) = \frac{x^2 - 1}{x^2 + 1} f ( x ) = x 2 + 1 x 2 − 1 on [ − 1 , 1 ] [-1, 1] [ − 1 , 1 ] *:
* f ( − 1 ) = 0 f(-1) = 0 f ( − 1 ) = 0 , f ( 1 ) = 0 f(1) = 0 f ( 1 ) = 0 . Denominator is never zero.
* f ′ ( x ) = 4 x ( x 2 + 1 ) 2 = 0 ⟹ c = 0 ∈ ( − 1 , 1 ) f'(x) = \frac{4x}{(x^2 + 1)^2} = 0 \implies c = 0 \in (-1, 1) f ′ ( x ) = ( x 2 + 1 ) 2 4 x = 0 ⟹ c = 0 ∈ ( − 1 , 1 )
* *Non-Differentiable Counterexample f ( x ) = ∣ x ∣ f(x) = |x| f ( x ) = ∣ x ∣ on [ − 1 , 1 ] [-1, 1] [ − 1 , 1 ] *:
* f ( − 1 ) = 1 f(-1) = 1 f ( − 1 ) = 1 , f ( 1 ) = 1 f(1) = 1 f ( 1 ) = 1 . However, f f f is not differentiable at x = 0 x = 0 x = 0 .
* Rolle's Theorem fails, and no point c ∈ ( − 1 , 1 ) c \in (-1, 1) c ∈ ( − 1 , 1 ) satisfies f ′ ( c ) = 0 f'(c) = 0 f ′ ( c ) = 0 Root Counting Principle :Between any two distinct real roots of a differentiable function f f f , there lies at least one real root of its derivative f ′ f' f ′ Generalization : If a differentiable function f f f has n n n distinct real roots, then f ′ f' f ′ has at least n − 1 n - 1 n − 1 distinct real roots.Example : For f ( x ) = x 3 − 3 x f(x) = x^3 - 3x f ( x ) = x 3 − 3 x on [ − 3 , 3 ] [-\sqrt{3}, \sqrt{3}] [ − 3 , 3 ] , f ( − 3 ) = 0 f(-\sqrt{3}) = 0 f ( − 3 ) = 0 and f ( 3 ) = 0 f(\sqrt{3}) = 0 f ( 3 ) = 0 . Derivative f ′ ( x ) = 3 ( x 2 − 1 ) = 0 f'(x) = 3(x^2 - 1) = 0 f ′ ( x ) = 3 ( x 2 − 1 ) = 0 gives c = ± 1 c = \pm 1 c = ± 1 , both lying inside ( − 3 , 3 ) (-\sqrt{3}, \sqrt{3}) ( − 3 , 3 ) .The Mean Value Theorem and Functional Bounds Mean Value Theorem (MVT) : Let f f f be a function satisfying:f f f is continuous on [ a , b ] [a, b] [ a , b ] f f f is differentiable on ( a , b ) (a, b) ( a , b ) Conclusion : There exists at least one c ∈ ( a , b ) c \in (a, b) c ∈ ( a , b ) such that:f ′ ( c ) = f ( b ) − f ( a ) b − a f'(c) = \frac{f(b) - f(a)}{b - a} f ′ ( c ) = b − a f ( b ) − f ( a ) Geometric Meaning : The instantaneous rate of change at c c c equals the average rate of change over [ a , b ] [a, b] [ a , b ] . The tangent line at c c c is parallel to the secant line joining ( a , f ( a ) ) (a, f(a)) ( a , f ( a )) and ( b , f ( b ) ) (b, f(b)) ( b , f ( b )) .Rolle's Theorem as a Special Case : If f ( a ) = f ( b ) f(a) = f(b) f ( a ) = f ( b ) , the secant slope is 0 b − a = 0 \frac{0}{b - a} = 0 b − a 0 = 0 , yielding f ′ ( c ) = 0 f'(c) = 0 f ′ ( c ) = 0 .MVT Worked Examples :Parabola f ( x ) = x 2 f(x) = x^2 f ( x ) = x 2 on [ 1 , 3 ] [1, 3] [ 1 , 3 ] :Secant slope: f ( 3 ) − f ( 1 ) 3 − 1 = 9 − 1 2 = 4 \frac{f(3) - f(1)}{3 - 1} = \frac{9 - 1}{2} = 4 3 − 1 f ( 3 ) − f ( 1 ) = 2 9 − 1 = 4 f ′ ( c ) = 2 c = 4 ⟹ c = 2 f'(c) = 2c = 4 \implies c = 2 f ′ ( c ) = 2 c = 4 ⟹ c = 2 Logarithm f ( x ) = ln ( x ) f(x) = \ln(x) f ( x ) = ln ( x ) on [ 1 , e ] [1, e] [ 1 , e ] :Secant slope: 1 − 0 e − 1 = 1 e − 1 \frac{1 - 0}{e - 1} = \frac{1}{e - 1} e − 1 1 − 0 = e − 1 1 f ′ ( c ) = 1 c = 1 e − 1 ⟹ c = e − 1 ∈ ( 1 , e ) f'(c) = \frac{1}{c} = \frac{1}{e - 1} \implies c = e - 1 \in (1, e) f ′ ( c ) = c 1 = e − 1 1 ⟹ c = e − 1 ∈ ( 1 , e ) Sine f ( x ) = sin ( x ) f(x) = \sin(x) f ( x ) = sin ( x ) on [ 0 , π / 2 ] [0, \pi/2] [ 0 , π /2 ] :Secant slope: 1 − 0 π / 2 − 0 = 2 π \frac{1 - 0}{\pi/2 - 0} = \frac{2}{\pi} π /2 − 0 1 − 0 = π 2 f ′ ( c ) = cos ( c ) = 2 π ⟹ c = arccos ( 2 π ) f'(c) = \cos(c) = \frac{2}{\pi} \implies c = \arccos\left(\frac{2}{\pi}\right) f ′ ( c ) = cos ( c ) = π 2 ⟹ c = arccos ( π 2 ) Square Root f ( x ) = x f(x) = \sqrt{x} f ( x ) = x on [ 1 , 4 ] [1, 4] [ 1 , 4 ] :Secant slope: 2 − 1 4 − 1 = 1 3 \frac{2 - 1}{4 - 1} = \frac{1}{3} 4 − 1 2 − 1 = 3 1 f ′ ( c ) = 1 2 c = 1 3 ⟹ 2 c = 3 ⟹ c = 9 / 4 f'(c) = \frac{1}{2\sqrt{c}} = \frac{1}{3} \implies 2\sqrt{c} = 3 \implies c = 9/4 f ′ ( c ) = 2 c 1 = 3 1 ⟹ 2 c = 3 ⟹ c = 9/4 Cubic with Two MVT Points f ( x ) = x 3 − 3 x f(x) = x^3 - 3x f ( x ) = x 3 − 3 x on [ − 2 , 2 ] [-2, 2] [ − 2 , 2 ] :Secant slope: 2 − ( − 2 ) 2 − ( − 2 ) = 1 \frac{2 - (-2)}{2 - (-2)} = 1 2 − ( − 2 ) 2 − ( − 2 ) = 1 f ′ ( c ) = 3 c 2 − 3 = 1 ⟹ 3 c 2 = 4 ⟹ c = ± 2 3 f'(c) = 3c^2 - 3 = 1 \implies 3c^2 = 4 \implies c = \pm \frac{2}{\sqrt{3}} f ′ ( c ) = 3 c 2 − 3 = 1 ⟹ 3 c 2 = 4 ⟹ c = ± 3 2 Applications and Corollaries of MVT :Speeding Ticket Argument : A vehicle traveling 180 miles 180\,\text{miles} 180 miles in 3 hours 3\,\text{hours} 3 hours has an average speed of 60 mph 60\,\text{mph} 60 mph . By MVT, its instantaneous speedometer reading was exactly 60 mph 60\,\text{mph} 60 mph at some point during the trip.Bounding Function Change : If ∣ f ′ ( x ) ∣ ≤ M |f'(x)| \le M ∣ f ′ ( x ) ∣ ≤ M for all x ∈ [ a , b ] x \in [a, b] x ∈ [ a , b ] , then:∣ f ( b ) − f ( a ) ∣ ≤ M ∣ b − a ∣ |f(b) - f(a)| \le M|b - a| ∣ f ( b ) − f ( a ) ∣ ≤ M ∣ b − a ∣ Example : For f ( x ) = sin ( x ) f(x) = \sin(x) f ( x ) = sin ( x ) , ∣ cos ( x ) ∣ ≤ 1 ⟹ ∣ sin ( b ) − sin ( a ) ∣ ≤ ∣ b − a ∣ |\cos(x)| \le 1 \implies |\sin(b) - \sin(a)| \le |b - a| ∣ cos ( x ) ∣ ≤ 1 ⟹ ∣ sin ( b ) − sin ( a ) ∣ ≤ ∣ b − a ∣ . For a = 1 , b = 1.02 a = 1, b = 1.02 a = 1 , b = 1.02 , ∣ sin ( 1.02 ) − sin ( 1 ) ∣ ≤ 0.02 |\sin(1.02) - \sin(1)| \le 0.02 ∣ sin ( 1.02 ) − sin ( 1 ) ∣ ≤ 0.02 Constant Function Theorem : If f ′ ( x ) = 0 f'(x) = 0 f ′ ( x ) = 0 for all x ∈ ( a , b ) x \in (a, b) x ∈ ( a , b ) , then f f f is constant on [ a , b ] [a, b] [ a , b ] .Proof : For any x 1 < x 2 x_1 < x_2 x 1 < x 2 in [ a , b ] [a, b] [ a , b ] , f ( x 2 ) − f ( x 1 ) x 2 − x 1 = f ′ ( c ) = 0 ⟹ f ( x 1 ) = f ( x 2 ) \frac{f(x_2) - f(x_1)}{x_2 - x_1} = f'(c) = 0 \implies f(x_1) = f(x_2) x 2 − x 1 f ( x 2 ) − f ( x 1 ) = f ′ ( c ) = 0 ⟹ f ( x 1 ) = f ( x 2 ) Monotonicity Theorem : If f ′ ( x ) > 0 f'(x) > 0 f ′ ( x ) > 0 on ( a , b ) (a, b) ( a , b ) , f f f is strictly increasing. If f ′ ( x ) < 0 f'(x) < 0 f ′ ( x ) < 0 on ( a , b ) (a, b) ( a , b ) , f f f is strictly decreasing.Convex Functions, Tangent Inequalities, and Optimization Geometric Definition of Convexity : A function f f f is convex on an interval I I I if for all x , y ∈ I x, y \in I x , y ∈ I and t ∈ [ 0 , 1 ] t \in [0, 1] t ∈ [ 0 , 1 ] :f ( t x + ( 1 − t ) y ) ≤ t f ( x ) + ( 1 − t ) f ( y ) f(tx + (1 - t)y) \le tf(x) + (1 - t)f(y) f ( t x + ( 1 − t ) y ) ≤ t f ( x ) + ( 1 − t ) f ( y ) Meaning : The graph of f f f lies entirely below or on any secant line segment joining two points on the curve.Concave Functions : A function f f f is concave if − f -f − f is convex. Its graph lies above its secant lines.Derivative Criteria for Convexity :For a differentiable function: f f f is convex if and only if f ′ f' f ′ is an increasing function. For a twice differentiable function: If f ′ ′ ( x ) ≥ 0 f''(x) \ge 0 f ′′ ( x ) ≥ 0 on I I I , then f f f is convex on I I I . If f ′ ′ ( x ) > 0 f''(x) > 0 f ′′ ( x ) > 0 , f f f is strictly convex. Convexity Examples :Exponential f ( x ) = e x f(x) = e^x f ( x ) = e x : f ′ ′ ( x ) = e x > 0 ⟹ e x f''(x) = e^x > 0 \implies e^x f ′′ ( x ) = e x > 0 ⟹ e x is strictly convex on R \mathbb{R} R .Negative Logarithm f ( x ) = − ln ( x ) f(x) = -\ln(x) f ( x ) = − ln ( x ) (x > 0 x > 0 x > 0 ) : f ′ ′ ( x ) = 1 x 2 > 0 ⟹ − ln ( x ) f''(x) = \frac{1}{x^2} > 0 \implies -\ln(x) f ′′ ( x ) = x 2 1 > 0 ⟹ − ln ( x ) is strictly convex ⟹ ln ( x ) \implies \ln(x) ⟹ ln ( x ) is concave on ( 0 , ∞ ) (0, \infty) ( 0 , ∞ ) .Fundamental Inequalities for Convex Functions :Tangent Line Inequality : If f f f is convex and differentiable, the graph lies entirely above every tangent line:f ( x ) ≥ f ( a ) + f ′ ( a ) ( x − a ) f(x) \ge f(a) + f'(a)(x - a) f ( x ) ≥ f ( a ) + f ′ ( a ) ( x − a ) Example : For f ( x ) = e x f(x) = e^x f ( x ) = e x at a = 0 a = 0 a = 0 : e x ≥ 1 + x e^x \ge 1 + x e x ≥ 1 + x Example : For f ( x ) = x 2 f(x) = x^2 f ( x ) = x 2 at a = 1 a = 1 a = 1 : x 2 ≥ 1 + 2 ( x − 1 ) = 2 x − 1 x^2 \ge 1 + 2(x - 1) = 2x - 1 x 2 ≥ 1 + 2 ( x − 1 ) = 2 x − 1 Secant Line Inequality : For a < x < b a < x < b a < x < b :f ( x ) ≤ b − x b − a f ( a ) + x − a b − a f ( b ) f(x) \le \frac{b - x}{b - a}f(a) + \frac{x - a}{b - a}f(b) f ( x ) ≤ b − a b − x f ( a ) + b − a x − a f ( b ) Uniqueness of Global Minimum : If f f f is strictly convex and differentiable on an open interval, any critical point c c c where f ′ ( c ) = 0 f'(c) = 0 f ′ ( c ) = 0 is the unique global minimum of f f f Example : For f ( x ) = x 2 + 2 x + 5 f(x) = x^2 + 2x + 5 f ( x ) = x 2 + 2 x + 5 , f ′ ′ ( x ) = 2 > 0 f''(x) = 2 > 0 f ′′ ( x ) = 2 > 0 (convex). Setting f ′ ( x ) = 2 x + 2 = 0 f'(x) = 2x + 2 = 0 f ′ ( x ) = 2 x + 2 = 0 gives x = − 1 x = -1 x = − 1 as the unique global minimum.Jensen's Inequality :Midpoint Version : For a convex function f f f :f ( x + y 2 ) ≤ f ( x ) + f ( y ) 2 f\left(\frac{x + y}{2}\right) \le \frac{f(x) + f(y)}{2} f ( 2 x + y ) ≤ 2 f ( x ) + f ( y ) General Version : For weights t i ≥ 0 t_i \ge 0 t i ≥ 0 with ∑ t i = 1 \sum t_i = 1 ∑ t i = 1 :f ( ∑ t i x i ) ≤ ∑ t i f ( x i ) f\left(\sum t_i x_i\right) \le \sum t_i f(x_i) f ( ∑ t i x i ) ≤ ∑ t i f ( x i ) Application to Square Function (f ( x ) = x 2 f(x) = x^2 f ( x ) = x 2 ) :( x + y 2 ) 2 ≤ x 2 + y 2 2 ⟹ ( x + y ) 2 ≤ 2 x 2 + 2 y 2 \left(\frac{x + y}{2}\right)^2 \le \frac{x^2 + y^2}{2} \implies (x + y)^2 \le 2x^2 + 2y^2 ( 2 x + y ) 2 ≤ 2 x 2 + y 2 ⟹ ( x + y ) 2 ≤ 2 x 2 + 2 y 2 Questions & Discussion Question 1 : Find the absolute extrema of f ( x ) = x 4 − 4 x 2 + 1 f(x) = x^4 - 4x^2 + 1 f ( x ) = x 4 − 4 x 2 + 1 on [ − 2 , 3 ] [-2, 3] [ − 2 , 3 ] .Solution : Compute f ′ ( x ) = 4 x 3 − 8 x = 4 x ( x 2 − 2 ) = 0 ⟹ x = 0 , ± 2 f'(x) = 4x^3 - 8x = 4x(x^2 - 2) = 0 \implies x = 0, \pm\sqrt{2} f ′ ( x ) = 4 x 3 − 8 x = 4 x ( x 2 − 2 ) = 0 ⟹ x = 0 , ± 2 .Evaluate candidates: f ( − 2 ) = 1 f(-2) = 1 f ( − 2 ) = 1 , f ( − 2 ) = − 3 f(-\sqrt{2}) = -3 f ( − 2 ) = − 3 , f ( 0 ) = 1 f(0) = 1 f ( 0 ) = 1 , f ( 2 ) = − 3 f(\sqrt{2}) = -3 f ( 2 ) = − 3 , f ( 3 ) = 46 f(3) = 46 f ( 3 ) = 46 Answer : Absolute maximum is 46 46 46 at x = 3 x = 3 x = 3 ; Absolute minimum is − 3 -3 − 3 at x = − 2 x = -\sqrt{2} x = − 2 and x = 2 x = \sqrt{2} x = 2 .Question 2 : Find the absolute extrema of g ( x ) = x 2 x 2 + 1 g(x) = \frac{x^2}{x^2 + 1} g ( x ) = x 2 + 1 x 2 on [ − 3 , 3 ] [-3, 3] [ − 3 , 3 ] .Solution : g ′ ( x ) = 2 x ( x 2 + 1 ) − x 2 ( 2 x ) ( x 2 + 1 ) 2 = 2 x ( x 2 + 1 ) 2 = 0 ⟹ x = 0 g'(x) = \frac{2x(x^2 + 1) - x^2(2x)}{(x^2 + 1)^2} = \frac{2x}{(x^2 + 1)^2} = 0 \implies x = 0 g ′ ( x ) = ( x 2 + 1 ) 2 2 x ( x 2 + 1 ) − x 2 ( 2 x ) = ( x 2 + 1 ) 2 2 x = 0 ⟹ x = 0 Evaluate candidates: g ( − 3 ) = 9 / 10 g(-3) = 9/10 g ( − 3 ) = 9/10 , g ( 0 ) = 0 g(0) = 0 g ( 0 ) = 0 , g ( 3 ) = 9 / 10 g(3) = 9/10 g ( 3 ) = 9/10 Answer : Absolute maximum is 9 / 10 9/10 9/10 at x = ± 3 x = \pm 3 x = ± 3 ; Absolute minimum is 0 0 0 at x = 0 x = 0 x = 0 Question 3 : Find the absolute extrema of h ( x ) = cos ( x ) − sin ( x ) h(x) = \cos(x) - \sin(x) h ( x ) = cos ( x ) − sin ( x ) on [ 0 , 2 π ] [0, 2\pi] [ 0 , 2 π ] .Solution : h ′ ( x ) = − sin ( x ) − cos ( x ) = 0 ⟹ tan ( x ) = − 1 ⟹ x = 3 π / 4 , 7 π / 4 h'(x) = -\sin(x) - \cos(x) = 0 \implies \tan(x) = -1 \implies x = 3\pi/4, 7\pi/4 h ′ ( x ) = − sin ( x ) − cos ( x ) = 0 ⟹ tan ( x ) = − 1 ⟹ x = 3 π /4 , 7 π /4 Evaluate candidates: h ( 0 ) = 1 h(0) = 1 h ( 0 ) = 1 , h ( 3 π / 4 ) = − 2 h(3\pi/4) = -\sqrt{2} h ( 3 π /4 ) = − 2 , h ( 7 π / 4 ) = 2 h(7\pi/4) = \sqrt{2} h ( 7 π /4 ) = 2 , h ( 2 π ) = 1 h(2\pi) = 1 h ( 2 π ) = 1 Answer : Absolute maximum is 2 \sqrt{2} 2 at x = 7 π / 4 x = 7\pi/4 x = 7 π /4 ; Absolute minimum is − 2 1 = − 2 \frac{-\sqrt{2}}{1} = -\sqrt{2} 1 − 2 = − 2 at x = 3 π / 4 x = 3\pi/4 x = 3 π /4 Question 4 : Practice logarithmic differentiation on the following expressions:y = ( x 2 + 3 ) x ⟹ ln ( y ) = x ln ( x 2 + 3 ) ⟹ y ′ = ( x 2 + 3 ) x [ ln ( x 2 + 3 ) + 2 x 2 x 2 + 3 ] y = (x^2 + 3)^x \implies \ln(y) = x\ln(x^2 + 3) \implies y' = (x^2 + 3)^x\left[\ln(x^2 + 3) + \frac{2x^2}{x^2 + 3}\right] y = ( x 2 + 3 ) x ⟹ ln ( y ) = x ln ( x 2 + 3 ) ⟹ y ′ = ( x 2 + 3 ) x [ ln ( x 2 + 3 ) + x 2 + 3 2 x 2 ] y = ( x − 1 ) 5 x 2 + 1 ( x + 4 ) 3 ⟹ y ′ = y [ 5 x − 1 + x x 2 + 1 − 3 x + 4 ] y = \frac{(x - 1)^5\sqrt{x^2 + 1}}{(x + 4)^3} \implies y' = y\left[\frac{5}{x - 1} + \frac{x}{x^2 + 1} - \frac{3}{x + 4}\right] y = ( x + 4 ) 3 ( x − 1 ) 5 x 2 + 1 ⟹ y ′ = y [ x − 1 5 + x 2 + 1 x − x + 4 3 ] y = x cos ( x ) ⟹ y ′ = x cos ( x ) [ cos ( x ) x − sin ( x ) ln ( x ) ] y = x^{\cos(x)} \implies y' = x^{\cos(x)}\left[\frac{\cos(x)}{x} - \sin(x)\ln(x)\right] y = x c o s ( x ) ⟹ y ′ = x c o s ( x ) [ x c o s ( x ) − sin ( x ) ln ( x ) ] y = ( tan ( x ) ) ln ( x ) ⟹ y ′ = ( tan ( x ) ) ln ( x ) [ ln ( tan ( x ) ) x + ln ( x ) sec 2 ( x ) tan ( x ) ] y = (\tan(x))^{\ln(x)} \implies y' = (\tan(x))^{\ln(x)}\left[\frac{\ln(\tan(x))}{x} + \frac{\ln(x)\sec^2(x)}{\tan(x)}\right] y = ( tan ( x ) ) l n ( x ) ⟹ y ′ = ( tan ( x ) ) l n ( x ) [ x l n ( t a n ( x )) + t a n ( x ) l n ( x ) s e c 2 ( x ) ] Question 5 : Prove that x 5 + x − 3 = 0 x^5 + x - 3 = 0 x 5 + x − 3 = 0 has a root in ( 1 , 2 ) (1, 2) ( 1 , 2 ) .Solution : Let f ( x ) = x 5 + x − 3 f(x) = x^5 + x - 3 f ( x ) = x 5 + x − 3 . f f f is continuous everywhere as a polynomial. f ( 1 ) = − 1 < 0 f(1) = -1 < 0 f ( 1 ) = − 1 < 0 and f ( 2 ) = 31 > 0 f(2) = 31 > 0 f ( 2 ) = 31 > 0 . By IVT, a root c ∈ ( 1 , 2 ) c \in (1, 2) c ∈ ( 1 , 2 ) exists.Question 6 : Prove that e − x = x e^{-x} = x e − x = x has a solution in ( 0 , 1 ) (0, 1) ( 0 , 1 ) .Solution : Let g ( x ) = e − x − x g(x) = e^{-x} - x g ( x ) = e − x − x . g ( 0 ) = 1 > 0 g(0) = 1 > 0 g ( 0 ) = 1 > 0 and g ( 1 ) = 1 / e − 1 < 0 g(1) = 1/e - 1 < 0 g ( 1 ) = 1/ e − 1 < 0 . By IVT, g ( c ) = 0 ⟹ e − c = c g(c) = 0 \implies e^{-c} = c g ( c ) = 0 ⟹ e − c = c for some c ∈ ( 0 , 1 ) c \in (0, 1) c ∈ ( 0 , 1 ) .Question 7 : Perform two bisection steps for x 3 − 4 x + 1 = 0 x^3 - 4x + 1 = 0 x 3 − 4 x + 1 = 0 starting on [ 0 , 1 ] [0, 1] [ 0 , 1 ] .Solution : f ( x ) = x 3 − 4 x + 1 f(x) = x^3 - 4x + 1 f ( x ) = x 3 − 4 x + 1 . f ( 0 ) = 1 f(0) = 1 f ( 0 ) = 1 , f ( 1 ) = − 2 f(1) = -2 f ( 1 ) = − 2 Step 1: Midpoint m 1 = 0.5 m_1 = 0.5 m 1 = 0.5 . f ( 0.5 ) = 0.125 − 2 + 1 = − 0.875 < 0 ⟹ f(0.5) = 0.125 - 2 + 1 = -0.875 < 0 \implies f ( 0.5 ) = 0.125 − 2 + 1 = − 0.875 < 0 ⟹ new interval [ 0 , 0.5 ] [0, 0.5] [ 0 , 0.5 ] Step 2: Midpoint m 2 = 0.25 m_2 = 0.25 m 2 = 0.25 . f ( 0.25 ) = 0.015625 − 1 + 1 = 0.015625 > 0 ⟹ f(0.25) = 0.015625 - 1 + 1 = 0.015625 > 0 \implies f ( 0.25 ) = 0.015625 − 1 + 1 = 0.015625 > 0 ⟹ new interval [ 0.25 , 0.5 ] [0.25, 0.5] [ 0.25 , 0.5 ] Question 8 : Calculate how many bisection steps guarantee an interval length below 10 − 4 10^{-4} 1 0 − 4 starting from [ 0 , 2 ] [0, 2] [ 0 , 2 ] .Solution : Initial length b − a = 2 b - a = 2 b − a = 2 . Need 2 2 n < 10 − 4 ⟹ 2 n − 1 > 10000 \frac{2}{2^n} < 10^{-4} \implies 2^{n - 1} > 10000 2 n 2 < 1 0 − 4 ⟹ 2 n − 1 > 10000 . Since 2 13 = 8192 2^{13} = 8192 2 13 = 8192 and 2 14 = 16384 2^{14} = 16384 2 14 = 16384 , set n − 1 = 14 ⟹ n = 15 n - 1 = 14 \implies n = 15 n − 1 = 14 ⟹ n = 15 steps.Question 9 : Analyze f ( x ) = x 4 − 4 x 3 + 10 f(x) = x^4 - 4x^3 + 10 f ( x ) = x 4 − 4 x 3 + 10 completely.Solution : f ′ ( x ) = 4 x 3 − 12 x 2 = 4 x 2 ( x − 3 ) = 0 ⟹ x = 0 , 3 f'(x) = 4x^3 - 12x^2 = 4x^2(x - 3) = 0 \implies x = 0, 3 f ′ ( x ) = 4 x 3 − 12 x 2 = 4 x 2 ( x − 3 ) = 0 ⟹ x = 0 , 3 Decreasing on ( − ∞ , 0 ) ∪ ( 0 , 3 ) (-\infty, 0) \cup (0, 3) ( − ∞ , 0 ) ∪ ( 0 , 3 ) ; Increasing on ( 3 , ∞ ) (3, \infty) ( 3 , ∞ ) x = 0 x = 0 x = 0 is not an extremum (f ′ f' f ′ retains negative sign); Local minimum at x = 3 x = 3 x = 3 with value f ( 3 ) = − 17 f(3) = -17 f ( 3 ) = − 17 f ′ ′ ( x ) = 12 x 2 − 24 x = 12 x ( x − 2 ) = 0 ⟹ x = 0 , 2 f''(x) = 12x^2 - 24x = 12x(x - 2) = 0 \implies x = 0, 2 f ′′ ( x ) = 12 x 2 − 24 x = 12 x ( x − 2 ) = 0 ⟹ x = 0 , 2 Concave up on ( − ∞ , 0 ) ∪ ( 2 , ∞ ) (-\infty, 0) \cup (2, \infty) ( − ∞ , 0 ) ∪ ( 2 , ∞ ) ; Concave down on ( 0 , 2 ) (0, 2) ( 0 , 2 ) Inflection points at ( 0 , 10 ) (0, 10) ( 0 , 10 ) and ( 2 , − 6 ) (2, -6) ( 2 , − 6 ) Question 10 : Determine where f ( x ) = x 4 − 4 x 2 f(x) = x^4 - 4x^2 f ( x ) = x 4 − 4 x 2 is convex or concave.Solution : f ′ ( x ) = 4 x 3 − 8 x ⟹ f ′ ′ ( x ) = 12 x 2 − 8 = 4 ( 3 x 2 − 2 ) f'(x) = 4x^3 - 8x \implies f''(x) = 12x^2 - 8 = 4(3x^2 - 2) f ′ ( x ) = 4 x 3 − 8 x ⟹ f ′′ ( x ) = 12 x 2 − 8 = 4 ( 3 x 2 − 2 ) f ′ ′ ( x ) = 0 ⟹ x = ± 2 / 3 f''(x) = 0 \implies x = \pm\sqrt{2/3} f ′′ ( x ) = 0 ⟹ x = ± 2/3 Convex (f ′ ′ ≥ 0 f'' \ge 0 f ′′ ≥ 0 ) on ( − ∞ , − 2 3 ] ∪ [ 2 3 , ∞ ) \left(-\infty, -\sqrt{\frac{2}{3}}\right] \cup \left[\sqrt{\frac{2}{3}}, \infty\right) ( − ∞ , − 3 2 ] ∪ [ 3 2 , ∞ ) Concave (f ′ ′ < 0 f'' < 0 f ′′ < 0 ) on ( − 2 3 , 2 3 ) \left(-\sqrt{\frac{2}{3}}, \sqrt{\frac{2}{3}}\right) ( − 3 2 , 3 2 )