Advanced Calculus and Linear Algebra: Integration, Extremal Analysis, and Differential Properties

Antiderivatives and Indefinite Integrals

  • Definition of Antiderivative: Given a function f(x)f(x), an antiderivative of f(x)f(x) is a function F(x)F(x) such that F′(x)=f(x)F'(x) = f(x).
    • Example: Since ddx(x5)=5x4\frac{d}{dx}(x^5) = 5x^4, an antiderivative of 5x45x^4 is x5x^5.
  • Indefinite Integral Notation: If F′(x)=f(x)F'(x) = f(x), then ∫f(x) dx=F(x)+C\int f(x)\,dx = F(x) + C.
  • Role of the Arbitrary Constant CC: The constant CC records all possible antiderivatives of f(x)f(x). It is not a decorative symbol; because the derivative of any constant is zero, ddx(F(x)+C)=F′(x)+0=f(x)\frac{d}{dx}(F(x) + C) = F'(x) + 0 = f(x).
  • Uniqueness Up to a Constant: Suppose F′(x)=G′(x)F'(x) = G'(x) on an interval. Then ddx(F(x)−G(x))=0\frac{d}{dx}(F(x) - G(x)) = 0. By the Mean Value Theorem, F(x)−G(x)=CF(x) - G(x) = C for some constant CC. Consequently, on an interval, all antiderivatives of a given function differ by a constant.
  • Visual Interpretation: Integration operates as the inverse process of differentiation.

Visual diagram showing differentiation and antidifferentiation

  • Linearity Rules: Antiderivatives satisfy linearity properties:
    • ∫(af(x)+bg(x)) dx=a∫f(x) dx+b∫g(x) dx\int (a f(x) + b g(x))\,dx = a \int f(x)\,dx + b \int g(x)\,dx
    • Example: ∫(6x2−4x+7) dx=2x3−2x2+7x+C\int (6x^2 - 4x + 7)\,dx = 2x^3 - 2x^2 + 7x + C
  • Power Rule for Antiderivatives: For any real exponent n≠−1n \neq -1:
    • ∫xn dx=xn+1n+1+C\int x^n\,dx = \frac{x^{n+1}}{n+1} + C
    • Example 1: ∫x7 dx=x88+C\int x^7\,dx = \frac{x^8}{8} + C
    • Example 2: ∫x dx=∫x1/2 dx=23x3/2+C\int \sqrt{x}\,dx = \int x^{1/2}\,dx = \frac{2}{3}x^{3/2} + C
  • The Exceptional Power n=−1n = -1: The standard power rule fails when n=−1n = -1 because it produces division by zero. Instead:
    • ∫1x dx=ln⁡(∣x∣)+C\int \frac{1}{x}\,dx = \ln(|x|) + C
    • Reason: ddxln⁡(∣x∣)=1x\frac{d}{dx}\ln(|x|) = \frac{1}{x} for all x≠0x \neq 0
  • Fundamental Table of Exponential and Logarithmic Antiderivatives:
    • ∫ex dx=ex+C\int e^x\,dx = e^x + C
    • ∫ax dx=axln⁡(a)+C\int a^x\,dx = \frac{a^x}{\ln(a)} + C for a>0,a≠1a > 0, a \neq 1
    • ∫1x dx=ln⁡(∣x∣)+C\int \frac{1}{x}\,dx = \ln(|x|) + C
    • ∫u′(x)u(x) dx=ln⁡(∣u(x)∣)+C\int \frac{u'(x)}{u(x)}\,dx = \ln(|u(x)|) + C
  • Fundamental Table of Trigonometric Antiderivatives:
    • ∫cos⁡(x) dx=sin⁡(x)+C\int \cos(x)\,dx = \sin(x) + C
    • ∫sin⁡(x) dx=−cos⁡(x)+C\int \sin(x)\,dx = -\cos(x) + C
    • ∫sec⁡2(x) dx=tan⁡(x)+C\int \sec^2(x)\,dx = \tan(x) + C
    • ∫csc⁡2(x) dx=−cot⁡(x)+C\int \csc^2(x)\,dx = -\cot(x) + C
    • ∫sec⁡(x)tan⁡(x) dx=sec⁡(x)+C\int \sec(x)\tan(x)\,dx = \sec(x) + C
    • ∫csc⁡(x)cot⁡(x) dx=−csc⁡(x)+C\int \csc(x)\cot(x)\,dx = -\csc(x) + C
  • Inverse Trigonometric Antiderivatives:
    • ∫dx1+x2=arctan⁡(x)+C\int \frac{dx}{1 + x^2} = \arctan(x) + C
    • ∫dx1−x2=arcsin⁡(x)+C\int \frac{dx}{\sqrt{1 - x^2}} = \arcsin(x) + C
    • General Form: ∫dxa2+x2=1aarctan⁡(xa)+C\int \frac{dx}{a^2 + x^2} = \frac{1}{a}\arctan\left(\frac{x}{a}\right) + C for a>0a > 0
  • Basic Integration Examples:
    • ∫(4x3−3x+5ex) dx=x4−3ln⁡(∣x∣)+5ex+C\int \left(4x^3 - \frac{3}{x} + 5e^x\right)\,dx = x^4 - 3\ln(|x|) + 5e^x + C
    • ∫(2cos⁡(x)−7sec⁡2(x)) dx=2sin⁡(x)−7tan⁡(x)+C\int \left(2\cos(x) - 7\sec^2(x)\right)\,dx = 2\sin(x) - 7\tan(x) + C
  • Verification Habit: The fastest method to detect integration errors is differentiating the anti-derivative result:
    • ddx(23x3/2+C)=23⋅32x1/2+0=x1/2=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}

The Substitution Method for Integration

  • Theoretical Principle: The substitution rule reverses the chain rule of differentiation. If u=g(x)u = g(x), then du=g′(x) dxdu = g'(x)\,dx, transforming the integral:
    • ∫f(g(x))g′(x) dx=∫f(u) du\int f(g(x))g'(x)\,dx = \int f(u)\,du
    • After computing the antiderivative in terms of uu, substitute back u=g(x)u = g(x).
  • Guidelines for Choosing uu:
    1. An expression situated inside a power, radical, exponential, logarithm, or trigonometric function.
    2. A denominator whose derivative (up to a constant multiple) appears in the numerator.
    3. A complicated expression whose derivative almost appears in the integrand.
    • Warning: If dudu does not match the remaining algebraic factors, substitution will not resolve the integral.
  • Direct Substitution Example: Evaluate ∫2xcos⁡(x2+1) dx\int 2x\cos(x^2 + 1)\,dx
    • Let u=x2+1u = x^2 + 1, then du=2x dxdu = 2x\,dx
    • ∫cos⁡(u) du=sin⁡(u)+C=sin⁡(x2+1)+C\int \cos(u)\,du = \sin(u) + C = \sin(x^2 + 1) + C
  • Constant Adjustment Example: Evaluate ∫xx2+4 dx\int x\sqrt{x^2 + 4}\,dx
    • Let u=x2+4u = x^2 + 4, then du=2x dx  ⟹  x dx=12dudu = 2x\,dx \implies x\,dx = \frac{1}{2}du
    • 12∫u1/2 du=12⋅23u3/2+C=13(x2+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
  • Logarithmic Form Example: Evaluate ∫3x2x3+5 dx\int \frac{3x^2}{x^3 + 5}\,dx
    • Let u=x3+5u = x^3 + 5, then du=3x2 dxdu = 3x^2\,dx
    • ∫duu=ln⁡(∣u∣)+C=ln⁡(∣x3+5∣)+C\int \frac{du}{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 uu:
    • ∫abf(g(x))g′(x) dx=∫g(a)g(b)f(u) du\int_a^b f(g(x))g'(x)\,dx = \int_{g(a)}^{g(b)} f(u)\,du
    • Safe Method 1: Convert limits to uu and evaluate entirely in terms of uu.
    • Safe Method 2: Find the antiderivative in terms of xx and evaluate using original limits aa and bb
  • Definite Integral Example: Evaluate ∫02xx2+1 dx\int_0^2 x\sqrt{x^2 + 1}\,dx
    • Let u=x2+1u = x^2 + 1, du=2x dx  ⟹  x dx=12dudu = 2x\,dx \implies x\,dx = \frac{1}{2}du
    • Convert limits: When x=0x = 0, u=02+1=1u = 0^2 + 1 = 1. When x=2x = 2, u=22+1=5u = 2^2 + 1 = 5
    • 12∫15u1/2 du=12[23u3/2]15=13(53/2−13/2)=55−13\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}
  • Mixed Variables Error: A uu-integral must never retain remaining factors of xx. For example, transforming ∫xx2+4 dx\int x\sqrt{x^2 + 4}\,dx into ∫xu du\int x\sqrt{u}\,du is mathematically invalid.

Advanced and Challenging Integration Techniques

  • Root Substitution Technique: Evaluate ∫e2xex+14 dx\int \frac{e^{2x}}{\sqrt[4]{e^x + 1}}\,dx
    • Set ex+1=t4  ⟹  ex=t4−1e^x + 1 = t^4 \implies e^x = t^4 - 1 and e2x=(t4−1)2e^{2x} = (t^4 - 1)^2
    • Differentiate ex+1=t4e^x + 1 = t^4 to get ex dx=4t3 dt  ⟹  dx=4t3ex dt=4t3t4−1 dte^x\,dx = 4t^3\,dt \implies dx = \frac{4t^3}{e^x}\,dt = \frac{4t^3}{t^4 - 1}\,dt
    • Substitute into integral: ∫(t4−1)2t⋅4t3t4−1 dt=4∫t2(t4−1) dt=4∫(t6−t2) dt\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
    • Integrate: 4(t77−t33)+C=47t7−43t3+C4\left(\frac{t^7}{7} - \frac{t^3}{3}\right) + C = \frac{4}{7}t^7 - \frac{4}{3}t^3 + C
    • Substitute back t=(ex+1)1/4t = (e^x + 1)^{1/4}:
    • 47(ex+1)7/4−43(ex+1)3/4+C\frac{4}{7}(e^x + 1)^{7/4} - \frac{4}{3}(e^x + 1)^{3/4} + C
  • Trigonometric-Rational Integral: Evaluate ∫dx2cos⁡2(x)+5sin⁡2(x)\int \frac{dx}{2\cos^2(x) + 5\sin^2(x)}
    • Set t=tan⁡(x)  ⟹  dt=sec⁡2(x) dx=(1+t2) dx  ⟹  dx=dt1+t2t = \tan(x) \implies dt = \sec^2(x)\,dx = (1 + t^2)\,dx \implies dx = \frac{dt}{1 + t^2}
    • Express trigonometric powers in terms of tt:
      • cos⁡2(x)=11+t2\cos^2(x) = \frac{1}{1 + t^2}
      • sin⁡2(x)=t21+t2\sin^2(x) = \frac{t^2}{1 + t^2}
    • Rewrite denominator: 2cos⁡2(x)+5sin⁡2(x)=2+5t21+t22\cos^2(x) + 5\sin^2(x) = \frac{2 + 5t^2}{1 + t^2}
    • Substitute: ∫dt1+t22+5t21+t2=∫dt2+5t2=12∫dt1+(52t)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}
    • Integrate: 12⋅152arctan⁡(52t)+C=110arctan⁡(52t)+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
    • Substitute back t=tan⁡(x)t = \tan(x): 110arctan⁡(52tan⁡(x))+C\frac{1}{\sqrt{10}}\arctan\left(\sqrt{\frac{5}{2}}\tan(x)\right) + C
  • Algebraic Power-Root Integral: Evaluate ∫x71+x24 dx\int \frac{x^7}{\sqrt[4]{1 + x^2}}\,dx
    • Let 1+x2=t4  ⟹  x2=t4−11 + x^2 = t^4 \implies x^2 = t^4 - 1 and 2x dx=4t3 dt  ⟹  x dx=2t3 dt2x\,dx = 4t^3\,dt \implies x\,dx = 2t^3\,dt
    • Decompose numerator: x7 dx=(x2)3(x dx)=(t4−1)3(2t3 dt)x^7\,dx = (x^2)^3(x\,dx) = (t^4 - 1)^3 (2t^3\,dt)
    • Substitute: ∫(t4−1)3⋅2t3 dtt=2∫t2(t4−1)3 dt\int \frac{(t^4 - 1)^3\cdot 2t^3\,dt}{t} = 2\int t^2(t^4 - 1)^3\,dt
    • Expand (t4−1)3=t12−3t8+3t4−1(t^4 - 1)^3 = t^{12} - 3t^8 + 3t^4 - 1:
      • 2∫t2(t12−3t8+3t4−1) dt=2∫(t14−3t10+3t6−t2) dt2\int t^2(t^{12} - 3t^8 + 3t^4 - 1)\,dt = 2\int (t^{14} - 3t^{10} + 3t^6 - t^2)\,dt
    • Integrate: 2(t1515−3t1111+3t77−t33)+C2\left(\frac{t^{15}}{15} - \frac{3t^{11}}{11} + \frac{3t^7}{7} - \frac{t^3}{3}\right) + C
    • Substitute back t=(1+x2)1/4t = (1 + x^2)^{1/4}.
    • 215(1+x2)15/4−611(1+x2)11/4+67(1+x2)7/4−23(1+x2)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
  • Logarithmic-Root Integral: Evaluate ∫(ln⁡(x))2x2+ln⁡(x)3 dx\int \frac{(\ln(x))^2}{x\sqrt[3]{2 + \ln(x)}}\,dx for x>e−2x > e^{-2}
    • Set 2+ln⁡(x)=t3  ⟹  ln⁡(x)=t3−22 + \ln(x) = t^3 \implies \ln(x) = t^3 - 2 and dxx=3t2 dt\frac{dx}{x} = 3t^2\,dt
    • Substitute: ∫(t3−2)2t⋅3t2 dt=3∫t(t3−2)2 dt=3∫t(t6−4t3+4) dt=3∫(t7−4t4+4t) dt\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
    • Integrate: 3(t88−4t55+2t2)+C=38t8−125t5+6t2+C3\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
    • Substitute back t=(2+ln⁡(x))1/3t = (2 + \ln(x))^{1/3}.
    • 38(2+ln⁡(x))8/3−125(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
  • Radicand Denominator Integral: Evaluate ∫x3x2+1+1 dx\int \frac{x^3}{\sqrt{x^2 + 1} + 1}\,dx
    • Set u=x2+1+1  ⟹  u−1=x2+1  ⟹  (u−1)2=x2+1  ⟹  x2=u2−2uu = \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
    • Differentiate x2=u2−2u  ⟹  2x dx=(2u−2) du  ⟹  x dx=(u−1) dux^2 = u^2 - 2u \implies 2x\,dx = (2u - 2)\,du \implies x\,dx = (u - 1)\,du
    • Decompose x3 dx=x2(x dx)=(u2−2u)(u−1) dux^3\,dx = x^2(x\,dx) = (u^2 - 2u)(u - 1)\,du
    • Substitute: ∫(u2−2u)(u−1)u du=∫(u−2)(u−1) du=∫(u2−3u+2) du\int \frac{(u^2 - 2u)(u - 1)}{u}\,du = \int (u - 2)(u - 1)\,du = \int (u^2 - 3u + 2)\,du
    • Integrate: u33−3u22+2u+C\frac{u^3}{3} - \frac{3u^2}{2} + 2u + C
    • Substitute back u=x2+1+1u = \sqrt{x^2 + 1} + 1
    • (x2+1+1)33−3(x2+1+1)22+2(x2+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
  • Rational Quadratic Square Integral: Evaluate ∫x3(x2+2x+2)2 dx\int \frac{x^3}{(x^2 + 2x + 2)^2}\,dx
    • Complete the square: x2+2x+2=(x+1)2+1x^2 + 2x + 2 = (x + 1)^2 + 1
    • Set u=x+1  ⟹  x=u−1,dx=du,x2+2x+2=u2+1u = x + 1 \implies x = u - 1, dx = du, x^2 + 2x + 2 = u^2 + 1
    • Expand numerator: (u−1)3=u3−3u2+3u−1(u - 1)^3 = u^3 - 3u^2 + 3u - 1
    • Rewrite integral: ∫u3−3u2+3u−1(u2+1)2 du\int \frac{u^3 - 3u^2 + 3u - 1}{(u^2 + 1)^2}\,du
    • Split into partial fractions:
      • ∫u3(u2+1)2 du=12ln⁡(u2+1)+12(u2+1)\int \frac{u^3}{(u^2 + 1)^2}\,du = \frac{1}{2}\ln(u^2 + 1) + \frac{1}{2(u^2 + 1)}
      • ∫−3u2(u2+1)2 du=−3(12arctan⁡(u)−u2(u2+1))\int \frac{-3u^2}{(u^2 + 1)^2}\,du = -3\left(\frac{1}{2}\arctan(u) - \frac{u}{2(u^2 + 1)}\right)
      • ∫3u(u2+1)2 du=−32(u2+1)\int \frac{3u}{(u^2 + 1)^2}\,du = -\frac{3}{2(u^2 + 1)}
      • ∫−1(u2+1)2 du=−12arctan⁡(u)−u2(u2+1)\int \frac{-1}{(u^2 + 1)^2}\,du = -\frac{1}{2}\arctan(u) - \frac{u}{2(u^2 + 1)}
    • Combine and simplify in variable uu:
      • 12ln⁡(u2+1)−32arctan⁡(u)−u2+3u−12(u2+1)+C\frac{1}{2}\ln(u^2 + 1) - \frac{3}{2}\arctan(u) - \frac{u^2 + 3u - 1}{2(u^2 + 1)} + C
    • Substitute back u=x+1u = x + 1
    • 12ln⁡(x2+2x+2)−32arctan⁡(x+1)−(x+1)2+3(x+1)−12(x2+2x+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

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.

Graph illustrating local and absolute extrema

  • Extreme Value Theorem (EVT): If ff is continuous on a closed interval [a,b][a, b], then ff attains both an absolute maximum and an absolute minimum on [a,b][a, b].
    • Formal Statement: There exist points c,d∈[a,b]c, d \in [a, b] such that f(c)≤f(x)≤f(d)f(c) \le f(x) \le f(d) for every x∈[a,b]x \in [a, b].
  • Necessity of Hypotheses:
    • Non-Closed Interval: The function f(x)=xf(x) = x on (0,1)(0, 1) has no absolute minimum or maximum because the endpoint boundaries 00 and 11 are excluded.
    • Discontinuity: The piecewise function f(x)=xf(x) = x for 0≤x<10 \le x < 1 and f(1)=0f(1) = 0 on [0,1][0, 1] lacks an absolute maximum because its values approach 11 without ever reaching it.
  • The Closed Interval Method: To find absolute extrema of a continuous function ff on [a,b][a, b]:
    1. Verify that ff is continuous on [a,b][a, b].
    2. Find all critical numbers of ff in the open interval (a,b)(a, b) where f′(x)=0f'(x) = 0 or f′(x)f'(x) does not exist.
    3. Evaluate f(x)f(x) at every critical number and at the endpoints aa and bb
    4. 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)=x3−3x2−9x+5f(x) = x^3 - 3x^2 - 9x + 5 on [−2,5][-2, 5]
    • Compute derivative: f′(x)=3x2−6x−9=3(x−3)(x+1)f'(x) = 3x^2 - 6x - 9 = 3(x - 3)(x + 1)
    • Critical numbers in (−2,5)(-2, 5): x=−1,3x = -1, 3
    • Evaluate inputs:
      • f(−2)=(−2)3−3(−2)2−9(−2)+5=3f(-2) = (-2)^3 - 3(-2)^2 - 9(-2) + 5 = 3
      • f(−1)=(−1)3−3(−1)2−9(−1)+5=10f(-1) = (-1)^3 - 3(-1)^2 - 9(-1) + 5 = 10
      • f(3)=(3)3−3(3)2−9(3)+5=−22f(3) = (3)^3 - 3(3)^2 - 9(3) + 5 = -22
      • f(5)=(5)3−3(5)2−9(5)+5=10f(5) = (5)^3 - 3(5)^2 - 9(5) + 5 = 10
    • Conclusion: Absolute maximum value is 1010 at x=−1x = -1 and x=5x = 5. Absolute minimum value is −22-22 at x=3x = 3.

Graph of cubic polynomial EVT example

  • EVT Example 2 (Trigonometric Function): Find absolute extrema of f(x)=sin⁡(x)+cos⁡(x)f(x) = \sin(x) + \cos(x) on [0,π][0, \pi]
    • Compute derivative: f′(x)=cos⁡(x)−sin⁡(x)=0  ⟹  tan⁡(x)=1f'(x) = \cos(x) - \sin(x) = 0 \implies \tan(x) = 1
    • Critical number in [0,π][0, \pi]: x=π/4x = \pi/4
    • Evaluate inputs: f(0)=1f(0) = 1, f(π/4)=2f(\pi/4) = \sqrt{2}, f(π)=−1f(\pi) = -1
    • Conclusion: Absolute maximum is 2\sqrt{2} at x=π/4x = \pi/4. Absolute minimum is −1-1 at x=πx = \pi.
  • EVT Example 3 (Radical Function): Find absolute extrema of f(x)=x(4−x)f(x) = \sqrt{x}(4 - x) on [0,4][0, 4]
    • Compute derivative for x>0x > 0: f′(x)=12x(4−x)−x=4−3x2xf'(x) = \frac{1}{2\sqrt{x}}(4 - x) - \sqrt{x} = \frac{4 - 3x}{2\sqrt{x}}
    • Critical numbers: x=4/3x = 4/3 (where f′=0f' = 0) and x=0x = 0 (endpoint where f′f' is undefined)
    • Evaluate inputs: f(0)=0f(0) = 0, f(4/3)=4/3(4−4/3)=1633f(4/3) = \sqrt{4/3}(4 - 4/3) = \frac{16}{3\sqrt{3}}, f(4)=0f(4) = 0
    • Conclusion: Absolute maximum is 1633\frac{16}{3\sqrt{3}} at x=4/3x = 4/3. Absolute minimum is 00 at x=0x = 0 and x=4x = 4
  • EVT Example 4 (Rational Function): Find absolute extrema of f(x)=xx2+1f(x) = \frac{x}{x^2 + 1} on [−2,2][-2, 2]
    • Compute derivative: f′(x)=(x2+1)−2x2(x2+1)2=1−x2(x2+1)2f'(x) = \frac{(x^2 + 1) - 2x^2}{(x^2 + 1)^2} = \frac{1 - x^2}{(x^2 + 1)^2}
    • Critical numbers: x=±1x = \pm 1
    • Evaluate inputs: f(−2)=−2/5f(-2) = -2/5, f(−1)=−1/2f(-1) = -1/2, f(1)=1/2f(1) = 1/2, f(2)=2/5f(2) = 2/5
    • Conclusion: Absolute maximum is 1/21/2 at x=1x = 1. Absolute minimum is −1/2-1/2 at x=−1x = -1.
  • EVT Example 5 (Exponential Function): Find absolute extrema of f(x)=xe−xf(x) = xe^{-x} on [0,4][0, 4]
    • Compute derivative: f′(x)=e−x−xe−x=e−x(1−x)f'(x) = e^{-x} - xe^{-x} = e^{-x}(1 - x)
    • Critical number: x=1x = 1
    • Evaluate inputs: f(0)=0f(0) = 0, f(1)=1/ef(1) = 1/e, f(4)=4/e4f(4) = 4/e^4
    • Conclusion: Absolute maximum is 1/e1/e at x=1x = 1. Absolute minimum is 00 at x=0x = 0
  • EVT Example 6 (Logarithmic Function): Find absolute extrema of f(x)=ln⁡(x)−xf(x) = \ln(x) - x on [1/2,4][1/2, 4]
    • Compute derivative: f′(x)=1x−1=1−xxf'(x) = \frac{1}{x} - 1 = \frac{1 - x}{x}
    • Critical number: x=1x = 1
    • Evaluate inputs: f(1/2)=−ln⁡(2)−1/2≈−1.193f(1/2) = -\ln(2) - 1/2 \approx -1.193, f(1)=−1f(1) = -1, f(4)=ln⁡(4)−4≈−2.614f(4) = \ln(4) - 4 \approx -2.614
    • Conclusion: Absolute maximum is −1-1 at x=1x = 1. Absolute minimum is ln⁡(4)−4\ln(4) - 4 at x=4x = 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)}).
  • Standard Procedure:
    1. Take the natural logarithm of both sides: ln⁡(y)=ln⁡(f(x))\ln(y) = \ln(f(x))
    2. Simplify the right side using logarithm expansion rules: ln⁡(AB)=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⁡(Ar)=rln⁡(A)\ln(A^r) = r\ln(A).
    3. Differentiate implicitly with respect to xx: y′y=ddx[ln⁡(f(x))]\frac{y'}{y} = \frac{d}{dx}[\ln(f(x))]
    4. Solve for y′y': y′=y⋅ddx[ln⁡(f(x))]y' = y \cdot \frac{d}{dx}[\ln(f(x))]
    5. Substitute the original expression for yy
  • Logarithmic Differentiation Examples:
    • Variable Power y=xxy = x^x (x>0x > 0):
      • ln⁡(y)=xln⁡(x)  ⟹  y′y=ln⁡(x)+1  ⟹  y′=xx(ln⁡(x)+1)\ln(y) = x\ln(x) \implies \frac{y'}{y} = \ln(x) + 1 \implies y' = x^x(\ln(x) + 1)
    • Trigonometric Power y=(sin⁡(x))xy = (\sin(x))^x (sin⁡(x)>0\sin(x) > 0):
      • ln⁡(y)=xln⁡(sin⁡(x))  ⟹  y′y=ln⁡(sin⁡(x))+xcot⁡(x)  ⟹  y′=(sin⁡(x))x[ln⁡(sin⁡(x))+xcot⁡(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)]
    • Product of Powers y=(x2+1)5(3x−1)4x+2y = (x^2 + 1)^5(3x - 1)^4\sqrt{x + 2}:
      • ln⁡(y)=5ln⁡(x2+1)+4ln⁡(3x−1)+12ln⁡(x+2)\ln(y) = 5\ln(x^2 + 1) + 4\ln(3x - 1) + \frac{1}{2}\ln(x + 2)
      • y′y=10xx2+1+123x−1+12(x+2)\frac{y'}{y} = \frac{10x}{x^2 + 1} + \frac{12}{3x - 1} + \frac{1}{2(x + 2)}
      • y′=(x2+1)5(3x−1)4x+2[10xx2+1+123x−1+12(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]
    • Complex Quotient y=x3x2+4(5x−2)7(x+1)2y = \frac{x^3\sqrt{x^2 + 4}}{(5x - 2)^7(x + 1)^2}:
      • ln⁡(y)=3ln⁡(x)+12ln⁡(x2+4)−7ln⁡(5x−2)−2ln⁡(x+1)\ln(y) = 3\ln(x) + \frac{1}{2}\ln(x^2 + 4) - 7\ln(5x - 2) - 2\ln(x + 1)
      • y′y=3x+xx2+4−355x−2−2x+1\frac{y'}{y} = \frac{3}{x} + \frac{x}{x^2 + 4} - \frac{35}{5x - 2} - \frac{2}{x + 1}
      • y′=y[3x+xx2+4−355x−2−2x+1]y' = y \left[\frac{3}{x} + \frac{x}{x^2 + 4} - \frac{35}{5x - 2} - \frac{2}{x + 1}\right]
    • Variable Radical Power y=(ln⁡(x))xy = (\ln(x))^{\sqrt{x}} (x>1x > 1):
      • ln⁡(y)=xln⁡(ln⁡(x))\ln(y) = \sqrt{x}\ln(\ln(x))
      • y′y=12xln⁡(ln⁡(x))+x⋅1xln⁡(x)=ln⁡(ln⁡(x))2x+1xln⁡(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′=(ln⁡(x))x[ln⁡(ln⁡(x))2x+1xln⁡(x)]y' = (\ln(x))^{\sqrt{x}} \left[\frac{\ln(\ln(x))}{2\sqrt{x}} + \frac{1}{\sqrt{x}\ln(x)}\right]
    • Exponential Base Power y=(x2+1)sin⁡(x)y = (x^2 + 1)^{\sin(x)}:
      • ln⁡(y)=sin⁡(x)ln⁡(x2+1)\ln(y) = \sin(x)\ln(x^2 + 1)
      • y′y=cos⁡(x)ln⁡(x2+1)+sin⁡(x)⋅2xx2+1\frac{y'}{y} = \cos(x)\ln(x^2 + 1) + \sin(x)\cdot\frac{2x}{x^2 + 1}
      • y′=(x2+1)sin⁡(x)[cos⁡(x)ln⁡(x2+1)+2xsin⁡(x)x2+1]y' = (x^2 + 1)^{\sin(x)} \left[\cos(x)\ln(x^2 + 1) + \frac{2x\sin(x)}{x^2 + 1}\right]
  • Monotonicity Analysis via f′f\frac{f'}{f}: If f(x)>0f(x) > 0, then f′(x)=f(x)ddx[ln⁡(f(x))]f'(x) = f(x)\frac{d}{dx}[\ln(f(x))]. Since f(x)>0f(x) > 0, the sign of f′(x)f'(x) is completely determined by the sign of f′(x)f(x)=ddx[ln⁡(f(x))]\frac{f'(x)}{f(x)} = \frac{d}{dx}[\ln(f(x))].
    • Example 1: f(x)=xx2+1f(x) = \frac{x}{x^2 + 1} for x>0x > 0
      • ln⁡(f)=ln⁡(x)−ln⁡(x2+1)  ⟹  f′f=1x−2xx2+1=1−x2x(x2+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)}
      • The sign depends on 1−x21 - x^2. Thus, ff is increasing on (0,1)(0, 1) and decreasing on (1,∞)(1, \infty).
    • Example 2: f(x)=x2e−xf(x) = x^2 e^{-x} for x>0x > 0
      • ln⁡(f)=2ln⁡(x)−x  ⟹  f′f=2x−1=2−xx\ln(f) = 2\ln(x) - x \implies \frac{f'}{f} = \frac{2}{x} - 1 = \frac{2 - x}{x}
      • ff is increasing on (0,2)(0, 2) and decreasing on (2,∞)(2, \infty).
    • Example 3: f(x)=x3(x+1)4f(x) = \frac{x^3}{(x + 1)^4} for x>0x > 0
      • ln⁡(f)=3ln⁡(x)−4ln⁡(x+1)  ⟹  f′f=3x−4x+1=3−xx(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)}
      • ff is increasing on (0,3)(0, 3) and decreasing on (3,∞)(3, \infty).
    • Example 4: f(x)=xa(1−x)bf(x) = x^a(1 - x)^b for 0<x<10 < x < 1 (a,b>0a, b > 0)
      • ln⁡(f)=aln⁡(x)+bln⁡(1−x)  ⟹  f′f=ax−b1−x=a−(a+b)xx(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)}
      • ff is increasing on (0,aa+b)\left(0, \frac{a}{a + b}\right) and decreasing on (aa+b,1)\left(\frac{a}{a + b}, 1\right).

The Intermediate Value Theorem and Numerical Root Finding

  • Intermediate Value Theorem (IVT): If ff is continuous on [a,b][a, b] and NN is any real number between f(a)f(a) and f(b)f(b), then there exists at least one value c∈(a,b)c \in (a, b) such that f(c) = N$.\n * *Root-Finding Variant*: If fiscontinuousonis continuous on[a, b]andandf(a)f(b) < 0(oppositesigns),thereexists(opposite signs), there existsc \in (a, b)suchthatsuch thatf(c) = 0$.
  • IVT Application Examples:
    • Polynomial Root: Show f(x)=x3+x−1f(x) = x^3 + x - 1 has a root in (0,1)(0, 1).
      • f(0)=−1<0f(0) = -1 < 0 and f(1)=1>0f(1) = 1 > 0. By IVT, a root c∈(0,1)c \in (0, 1) exists.
    • Trigonometric Root: Show f(x)=cos⁡(x)−xf(x) = \cos(x) - x has a root in (0,1)(0, 1).
      • f(0)=1>0f(0) = 1 > 0 and f(1)=cos⁡(1)−1<0f(1) = \cos(1) - 1 < 0. By IVT, cos⁡(c)=c\cos(c) = c for some c∈(0,1)c \in (0, 1).
    • Logarithmic Equation: Show ln⁡(x)=x−2\ln(x) = x - 2 has a solution in (1,4)(1, 4).
      • Define f(x)=ln⁡(x)−x+2f(x) = \ln(x) - x + 2. f(1)=1>0f(1) = 1 > 0 and f(4)=ln⁡(4)−2≈−0.614<0f(4) = \ln(4) - 2 \approx -0.614 < 0. IVT guarantees a root.
    • Sequential Sign Testing: For f(x)=x3−2x−5f(x) = x^3 - 2x - 5:
      • f(2)=−1<0f(2) = -1 < 0 and f(3)=16>0  ⟹  f(3) = 16 > 0 \implies root lies in (2,3)(2, 3).
      • Midpoint x=2.5x = 2.5: f(2.5)=5.625>0  ⟹  f(2.5) = 5.625 > 0 \implies root lies in (2,2.5)(2, 2.5).
      • Midpoint x=2.25x = 2.25: f(2.25)=1.890625>0  ⟹  f(2.25) = 1.890625 > 0 \implies root lies in (2,2.25)(2, 2.25).
  • Bisection Method Procedure:
    1. Start with an interval [a,b][a, b] where f(a)f(b)<0f(a)f(b) < 0
    2. Calculate the midpoint m=a+b2m = \frac{a + b}{2}
    3. If f(m)=0f(m) = 0, mm is the exact root.
    4. If f(a)f(m)<0f(a)f(m) < 0, the root lies in [a,m][a, m]. Set new interval to [a,m][a, m].
    5. If f(m)f(b)<0f(m)f(b) < 0, the root lies in [m,b][m, b]. Set new interval to [m,b][m, b].
    6. Repeat sequentially. Each step halves the interval length.
  • Bisection Error Analysis:
    • After nn bisection steps, the interval length is b−a2n\frac{b - a}{2^n}.
    • The maximum error when estimating the root by the midpoint of the final interval is b−a2n+1\frac{b - a}{2^{n + 1}}.
    • Step Calculation Example: To guarantee interval length below ε=0.001\varepsilon = 0.001 starting from [2,3][2, 3]:
      • 12n<0.001  ⟹  2n>1000\frac{1}{2^n} < 0.001 \implies 2^n > 1000. Since 210=10242^{10} = 1024, 1010 bisection steps are required.
  • Bisection Worked Example 1 (x3+x−1=0x^3 + x - 1 = 0 on [0,1][0, 1]):
    • Initial: f(0)=−1f(0) = -1, f(1)=1f(1) = 1
    • Step 1: m1=0.5m_1 = 0.5, f(0.5)=−0.375<0  ⟹  f(0.5) = -0.375 < 0 \implies interval [0.5,1][0.5, 1]
    • Step 2: m2=0.75m_2 = 0.75, f(0.75)=0.171875>0  ⟹  f(0.75) = 0.171875 > 0 \implies interval [0.5,0.75][0.5, 0.75]
    • Step 3: m3=0.625m_3 = 0.625, f(0.625)=−0.130859<0  ⟹  f(0.625) = -0.130859 < 0 \implies interval [0.625,0.75][0.625, 0.75]
    • Step 4: m4=0.6875m_4 = 0.6875, f(0.6875)≈0.01245>0  ⟹  f(0.6875) \approx 0.01245 > 0 \implies interval [0.625,0.6875][0.625, 0.6875]
    • Midpoint estimate: x≈0.625+0.68752=0.65625x \approx \frac{0.625 + 0.6875}{2} = 0.65625
  • Bisection Worked Example 2 (cos⁡(x)=x\cos(x) = x on [0,1][0, 1]):
    • Initial: f(0)=1>0f(0) = 1 > 0, f(1)=cos⁡(1)−1<0f(1) = \cos(1) - 1 < 0
    • Step 1: m1=0.5m_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 interval [0.5,1][0.5, 1]
    • Step 2: m2=0.75m_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 interval [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)+CF(x) + C.
    • A definite integral ∫abf(x) dx\int_a^b f(x)\,dx is a numerical value representing net signed area.
  • The Accumulation Function: Fix aa and define A(x)=∫axf(t) dtA(x) = \int_a^x f(t)\,dt

Accumulation Function Diagram

  • Difference Quotient Derivation:
    • A(x+h)−A(x)=∫xx+hf(t) dtA(x + h) - A(x) = \int_x^{x + h} f(t)\,dt
    • For small hh, the strip area is approximated by f(x)hf(x)h, giving A(x+h)−A(x)h≈f(x)\frac{A(x + h) - A(x)}{h} \approx f(x)
    • By the Mean Value Theorem for integrals, ∫xx+hf(t) dt=f(ch)h\int_x^{x + h} f(t)\,dt = f(c_h)h for some chc_h between xx and x+hx + h.
    • Divide by hh: A(x+h)−A(x)h=f(ch)\frac{A(x + h) - A(x)}{h} = f(c_h). Taking $h \to 0forcesforcesc_h \to x,socontinuitygives, so continuity givesA'(x) = f(x).\n* **Fundamental Theorem of Calculus, Part I (FTC I)**:\n * If fiscontinuousonis continuous on[a, b]andandA(x) = \int_a^x f(t)\,dt,then, thenA'(x) = f(x).\n * *Core Principle*: Differentiation reverses integration accumulation.\n* **Fundamental Theorem of Calculus, Part II (FTC II)**:\n * If fiscontinuousonis continuous on[a, b]andandFisanyantiderivativeofis any antiderivative off((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.Then. ThenA' = f = F',meaning, meaningA(x) - F(x) = C.Since. SinceA(a) = 0,,C = -F(a).Therefore. ThereforeA(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,let, letu = 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,evaluatingdirectlyas, evaluating directly ase^{-x^2}isincorrect.Theupperlimitis incorrect. The upper limitx^2requiresmultiplyingbyitsderivativerequires multiplying by its derivative2x,yielding, yieldingF'(x) = 2xe^{-x^4}.\n\n# Riemann Sums and Definite Integrals\n\n* **Partition Construction**: Divide [a, b]intointonsubintervalsofequalwidthsubintervals of equal width\Delta x = \frac{b - a}{n},withgridpoints, with grid pointsx_k = a + k\Delta x.\n* **Riemann Sum Definition**: On each subinterval [x_{k-1}, x_k],pickasamplepoint, pick a sample pointx_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 + 1onon[0, 2])**:\n * Width: \Delta x = \frac{2}{n},gridpoints, grid pointsx_k = \frac{2k}{n}\n * *Four Subintervals (n = 4, \Delta x = 1/2)∗:Endpointsare)*: Endpoints are0, 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}.As. Asn \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}andandx_k = 1 + \frac{k}{n}onintervalon interval[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 = 25definedefineyimplicitlyasafunctionofimplicitly as a function ofx.Implicitdifferentiationyields. Implicit differentiation yields\frac{dy}{dx}directlywithoutrequiringexplicitsolutionfordirectly without requiring explicit solution fory\n* **Chain Rule Mechanics**: Treating yasasy(x),differentiationappliesthepowerchainrule:, differentiation applies the power chain rule:\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'wheneverdifferentiatingaterminvolvingwhenever differentiating a term involvingy\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![Circle graph with tangent line at (3,4)](https://assets.knowt.com/pdf-flow-prod/e72e80d4-4859-4029-b853-d8a477f51b24-figures/3.png)\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) > 0onanintervalon an interval\implies f is strictly increasing on that interval.\n * f'(x) < 0onanintervalon an interval\implies f is strictly decreasing on that interval.\n* **Critical Numbers**: A number cinthedomainofin the domain offisacriticalnumberifis a critical number iff'(c) = 0ororf'(c) does not exist. Critical numbers are candidates for local extrema.\n* **First Derivative Test**: Let cbeacriticalnumberofacontinuousfunctionbe a critical number of a continuous functionf:\n * If f'changessignfrompositivetonegativeatchanges sign from positive to negative atc,,fhasalocalmaximumathas a local maximum atc\n * If f'changessignfromnegativetopositiveatchanges sign from negative to positive atc,,fhasalocalminimumathas a local minimum atc\n * If f'retainsthesamesignonbothsidesofretains the same sign on both sides ofc,,fhasnolocalextremumathas no local extremum atc\n * *Example 1*: f(x) = x^3 - 3x \implies f'(x) = 3(x - 1)(x + 1).Localmaxat. Local max at(-1, 2),localminat, local min at(1, -2).\n * *Example 2*: f(x) = x^4 - 2x^2 \implies f'(x) = 4x(x - 1)(x + 1).Criticalnumbers. Critical numbersx = -1, 0, 1.Localminimaat. Local minima atx = \pm 1,localmaxat, local max atx = 0\n * *Example 3*: f(x) = |x| \implies f'(x) = -1forforx < 0andandf'(x) = 1forforx > 0.Derivativedoesnotexistat. Derivative does not exist atx = 0.Signchanges. Sign changes-$ to ++, so x=0x = 0 is a local minimum.
  • Concavity and Inflection Points:
    • Concave Up: f′′(x)>0f''(x) > 0 (slopes f′f' are increasing). Graph lies above tangent lines.
    • Concave Down: f′′(x)<0f''(x) < 0 (slopes f′f' are decreasing). Graph lies below tangent lines.
    • Inflection Point: A point where the graph changes concavity and ff is continuous.
    • Necessary Condition: Inflection can only occur where f′′(c)=0f''(c) = 0 or f′′(c)f''(c) does not exist, provided f′′f'' changes sign across cc
    • Example 1: f(x)=x4−4x3  ⟹  f′′(x)=12x(x−2)f(x) = x^4 - 4x^3 \implies f''(x) = 12x(x - 2). Concave up on (−∞,0)∪(2,∞)(-\infty, 0) \cup (2, \infty), concave down on (0,2)(0, 2). Inflection points at x=0x = 0 and x=2x = 2
    • Example 2: f(x)=x3  ⟹  f′′(x)=6xf(x) = x^3 \implies f''(x) = 6x. Inflection point at (0,0)(0, 0)
    • Example 3 (f′′=0f'' = 0 without Inflection): f(x)=x4  ⟹  f′′(x)=12x2f(x) = x^4 \implies f''(x) = 12x^2. Although f′′(0)=0f''(0) = 0, f′′(x)>0f''(x) > 0 on both sides of 00. The graph is concave up everywhere; (0,0)(0, 0) is not an inflection point.
  • Second Derivative Test: Suppose f′(c)=0f'(c) = 0
    • If f′′(c)>0f''(c) > 0, ff has a local minimum at cc
    • If f′′(c)<0f''(c) < 0, ff has a local maximum at cc
    • If f′′(c)=0f''(c) = 0, the test is inconclusive (use the First Derivative Test).

Complete Curve Analysis and Particle Motion

  • Curve Analysis Procedure:
    1. Determine domain and intercepts.
    2. Compute f′(x)f'(x) and find critical numbers.
    3. Build a sign chart for f′(x)f'(x) to establish increasing and decreasing intervals.
    4. Apply the First/Second Derivative Test to classify local extrema.
    5. Compute f′′(x)f''(x) and locate potential inflection points.
    6. Build a sign chart for f′′(x)f''(x) to establish concavity intervals.
    7. Sketch graph integrating all gathered behavior.
  • Complete Analysis Example (f(x)=x3−6x2+9xf(x) = x^3 - 6x^2 + 9x):
    • f′(x)=3x2−12x+9=3(x−1)(x−3)f'(x) = 3x^2 - 12x + 9 = 3(x - 1)(x - 3). Critical numbers: x=1,3x = 1, 3
    • Increasing on (−∞,1)∪(3,∞)(-\infty, 1) \cup (3, \infty); Decreasing on (1,3)(1, 3)
    • Local maximum at (1,4)(1, 4); Local minimum at (3,0)(3, 0)
    • f′′(x)=6x−12=6(x−2)f''(x) = 6x - 12 = 6(x - 2)
    • Concave down on (−∞,2)(-\infty, 2); Concave up on (2,∞)(2, \infty)
    • Inflection point at (2,2)(2, 2)
  • Application to Motion Along a Line:
    • Position s(t)s(t), Velocity v(t)=s′(t)v(t) = s'(t), Acceleration a(t)=s′′(t)=v′(t)a(t) = s''(t) = v'(t)
    • Example: s(t)=t3−6t2+9ts(t) = t^3 - 6t^2 + 9t
      • v(t)=3(t−1)(t−3)v(t) = 3(t - 1)(t - 3), a(t)=6(t−2)a(t) = 6(t - 2)
      • Moving forward (v(t)>0v(t) > 0) on (0,1)∪(3,∞)(0, 1) \cup (3, \infty)
      • Moving backward (v(t)<0v(t) < 0) on (1,3)(1, 3)
      • Particle changes direction at t=1t = 1 and t=3t = 3

Rolle's Theorem and Root Counting

  • Connecting Local and Global Properties: Local derivative values impose strict structural bounds on overall global graph behavior.

Global secant vs local slopes curve

  • Rolle's Theorem: Let ff be a function satisfying:
    1. ff is continuous on the closed interval [a,b][a, b]
    2. ff is differentiable on the open interval (a,b)(a, b)
    3. f(a)=f(b)f(a) = f(b)
    • Conclusion: There exists at least one value c∈(a,b)c \in (a, b) such that f′(c)=0f'(c) = 0

Rolle's Theorem Diagram

  • Non-Uniqueness Warning: Rolle's Theorem guarantees the existence of at least one horizontal tangent, but there may be multiple valid values of cc
  • Rolle's Theorem Worked Examples:
    • Polynomial f(x)=x2−4x+3f(x) = x^2 - 4x + 3 on [1,3][1, 3]:
      • f(1)=0f(1) = 0, f(3)=0f(3) = 0. Polynomial is continuous and differentiable.
      • f′(x)=2x−4=0  ⟹  c=2∈(1,3)f'(x) = 2x - 4 = 0 \implies c = 2 \in (1, 3)

Graph of parabola with horizontal tangent at c=2

*   *Trigonometric f(x)=sin⁡(x)f(x) = \sin(x) on [0,π][0, \pi]*:
    *   f(0)=0f(0) = 0, f(π)=0f(\pi) = 0
    *   f′(x)=cos⁡(x)=0  ⟹  c=π/2∈(0,π)f'(x) = \cos(x) = 0 \implies c = \pi/2 \in (0, \pi)
*   *Rational f(x)=x2−1x2+1f(x) = \frac{x^2 - 1}{x^2 + 1} on [−1,1][-1, 1]*:
    *   f(−1)=0f(-1) = 0, f(1)=0f(1) = 0. Denominator is never zero.
    *   f′(x)=4x(x2+1)2=0  ⟹  c=0∈(−1,1)f'(x) = \frac{4x}{(x^2 + 1)^2} = 0 \implies c = 0 \in (-1, 1)
*   *Non-Differentiable Counterexample f(x)=∣x∣f(x) = |x| on [−1,1][-1, 1]*:
    *   f(−1)=1f(-1) = 1, f(1)=1f(1) = 1. However, ff is not differentiable at x=0x = 0.
    *   Rolle's Theorem fails, and no point c∈(−1,1)c \in (-1, 1) satisfies f′(c)=0f'(c) = 0
  • Root Counting Principle:
    • Between any two distinct real roots of a differentiable function ff, there lies at least one real root of its derivative f′f'
    • Generalization: If a differentiable function ff has nn distinct real roots, then f′f' has at least n−1n - 1 distinct real roots.
    • Example: For f(x)=x3−3xf(x) = x^3 - 3x on [−3,3][-\sqrt{3}, \sqrt{3}], f(−3)=0f(-\sqrt{3}) = 0 and f(3)=0f(\sqrt{3}) = 0. Derivative f′(x)=3(x2−1)=0f'(x) = 3(x^2 - 1) = 0 gives c=±1c = \pm 1, both lying inside (−3,3)(-\sqrt{3}, \sqrt{3}).

The Mean Value Theorem and Functional Bounds

  • Mean Value Theorem (MVT): Let ff be a function satisfying:
    1. ff is continuous on [a,b][a, b]
    2. ff is differentiable on (a,b)(a, b)
    • Conclusion: There exists at least one c∈(a,b)c \in (a, b) such that:
    • f′(c)=f(b)−f(a)b−af'(c) = \frac{f(b) - f(a)}{b - a}
    • Geometric Meaning: The instantaneous rate of change at cc equals the average rate of change over [a,b][a, b]. The tangent line at cc is parallel to the secant line joining (a,f(a))(a, f(a)) and (b,f(b))(b, f(b)).
  • Rolle's Theorem as a Special Case: If f(a)=f(b)f(a) = f(b), the secant slope is 0b−a=0\frac{0}{b - a} = 0, yielding f′(c)=0f'(c) = 0.
  • MVT Worked Examples:
    • Parabola f(x)=x2f(x) = x^2 on [1,3][1, 3]:
      • Secant slope: f(3)−f(1)3−1=9−12=4\frac{f(3) - f(1)}{3 - 1} = \frac{9 - 1}{2} = 4
      • f′(c)=2c=4  ⟹  c=2f'(c) = 2c = 4 \implies c = 2
    • Logarithm f(x)=ln⁡(x)f(x) = \ln(x) on [1,e][1, e]:
      • Secant slope: 1−0e−1=1e−1\frac{1 - 0}{e - 1} = \frac{1}{e - 1}
      • f′(c)=1c=1e−1  ⟹  c=e−1∈(1,e)f'(c) = \frac{1}{c} = \frac{1}{e - 1} \implies c = e - 1 \in (1, e)
    • Sine f(x)=sin⁡(x)f(x) = \sin(x) on [0,π/2][0, \pi/2]:
      • Secant slope: 1−0π/2−0=2π\frac{1 - 0}{\pi/2 - 0} = \frac{2}{\pi}
      • f′(c)=cos⁡(c)=2π  ⟹  c=arccos⁡(2π)f'(c) = \cos(c) = \frac{2}{\pi} \implies c = \arccos\left(\frac{2}{\pi}\right)
    • Square Root f(x)=xf(x) = \sqrt{x} on [1,4][1, 4]:
      • Secant slope: 2−14−1=13\frac{2 - 1}{4 - 1} = \frac{1}{3}
      • f′(c)=12c=13  ⟹  2c=3  ⟹  c=9/4f'(c) = \frac{1}{2\sqrt{c}} = \frac{1}{3} \implies 2\sqrt{c} = 3 \implies c = 9/4
    • Cubic with Two MVT Points f(x)=x3−3xf(x) = x^3 - 3x on [−2,2][-2, 2]:
      • Secant slope: 2−(−2)2−(−2)=1\frac{2 - (-2)}{2 - (-2)} = 1
      • f′(c)=3c2−3=1  ⟹  3c2=4  ⟹  c=±23f'(c) = 3c^2 - 3 = 1 \implies 3c^2 = 4 \implies c = \pm \frac{2}{\sqrt{3}}
  • Applications and Corollaries of MVT:
    • Speeding Ticket Argument: A vehicle traveling 180 miles180\,\text{miles} in 3 hours3\,\text{hours} has an average speed of 60 mph60\,\text{mph}. By MVT, its instantaneous speedometer reading was exactly 60 mph60\,\text{mph} at some point during the trip.
    • Bounding Function Change: If ∣f′(x)∣≤M|f'(x)| \le M for all x∈[a,b]x \in [a, b], then:
      • ∣f(b)−f(a)∣≤M∣b−a∣|f(b) - f(a)| \le M|b - a|
      • Example: For 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|. For a=1,b=1.02a = 1, b = 1.02, ∣sin⁡(1.02)−sin⁡(1)∣≤0.02|\sin(1.02) - \sin(1)| \le 0.02
    • Constant Function Theorem: If f′(x)=0f'(x) = 0 for all x∈(a,b)x \in (a, b), then ff is constant on [a,b][a, b].
      • Proof: For any x1<x2x_1 < x_2 in [a,b][a, b], f(x2)−f(x1)x2−x1=f′(c)=0  ⟹  f(x1)=f(x2)\frac{f(x_2) - f(x_1)}{x_2 - x_1} = f'(c) = 0 \implies f(x_1) = f(x_2)
    • Monotonicity Theorem: If f′(x)>0f'(x) > 0 on (a,b)(a, b), ff is strictly increasing. If f′(x)<0f'(x) < 0 on (a,b)(a, b), ff is strictly decreasing.

Convex Functions, Tangent Inequalities, and Optimization

  • Geometric Definition of Convexity: A function ff is convex on an interval II if for all x,y∈Ix, y \in I and t∈[0,1]t \in [0, 1]:
    • f(tx+(1−t)y)≤tf(x)+(1−t)f(y)f(tx + (1 - t)y) \le tf(x) + (1 - t)f(y)
    • Meaning: The graph of ff lies entirely below or on any secant line segment joining two points on the curve.
  • Concave Functions: A function ff is concave if −f-f is convex. Its graph lies above its secant lines.
  • Derivative Criteria for Convexity:
    • For a differentiable function: ff is convex if and only if f′f' is an increasing function.
    • For a twice differentiable function: If f′′(x)≥0f''(x) \ge 0 on II, then ff is convex on II. If f′′(x)>0f''(x) > 0, ff is strictly convex.
  • Convexity Examples:
    • Exponential f(x)=exf(x) = e^x: f′′(x)=ex>0  ⟹  exf''(x) = e^x > 0 \implies e^x is strictly convex on R\mathbb{R}.
    • Negative Logarithm f(x)=−ln⁡(x)f(x) = -\ln(x) (x>0x > 0): f′′(x)=1x2>0  ⟹  −ln⁡(x)f''(x) = \frac{1}{x^2} > 0 \implies -\ln(x) is strictly convex   ⟹  ln⁡(x)\implies \ln(x) is concave on (0,∞)(0, \infty).
  • Fundamental Inequalities for Convex Functions:
    • Tangent Line Inequality: If ff 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)
      • Example: For f(x)=exf(x) = e^x at a=0a = 0: ex≥1+xe^x \ge 1 + x
      • Example: For f(x)=x2f(x) = x^2 at a=1a = 1: x2≥1+2(x−1)=2x−1x^2 \ge 1 + 2(x - 1) = 2x - 1
    • Secant Line Inequality: For a<x<ba < x < b:
      • f(x)≤b−xb−af(a)+x−ab−af(b)f(x) \le \frac{b - x}{b - a}f(a) + \frac{x - a}{b - a}f(b)
  • Uniqueness of Global Minimum: If ff is strictly convex and differentiable on an open interval, any critical point cc where f′(c)=0f'(c) = 0 is the unique global minimum of ff
    • Example: For f(x)=x2+2x+5f(x) = x^2 + 2x + 5, f′′(x)=2>0f''(x) = 2 > 0 (convex). Setting f′(x)=2x+2=0f'(x) = 2x + 2 = 0 gives x=−1x = -1 as the unique global minimum.
  • Jensen's Inequality:
    • Midpoint Version: For a convex function ff:
      • f(x+y2)≤f(x)+f(y)2f\left(\frac{x + y}{2}\right) \le \frac{f(x) + f(y)}{2}
    • General Version: For weights ti≥0t_i \ge 0 with ∑ti=1\sum t_i = 1:
      • f(∑tixi)≤∑tif(xi)f\left(\sum t_i x_i\right) \le \sum t_i f(x_i)
    • Application to Square Function (f(x)=x2f(x) = x^2):
      • (x+y2)2≤x2+y22  ⟹  (x+y)2≤2x2+2y2\left(\frac{x + y}{2}\right)^2 \le \frac{x^2 + y^2}{2} \implies (x + y)^2 \le 2x^2 + 2y^2

Questions & Discussion

  • Question 1: Find the absolute extrema of f(x)=x4−4x2+1f(x) = x^4 - 4x^2 + 1 on [−2,3][-2, 3].
    • Solution: Compute f′(x)=4x3−8x=4x(x2−2)=0  ⟹  x=0,±2f'(x) = 4x^3 - 8x = 4x(x^2 - 2) = 0 \implies x = 0, \pm\sqrt{2}.
    • Evaluate candidates: f(−2)=1f(-2) = 1, f(−2)=−3f(-\sqrt{2}) = -3, f(0)=1f(0) = 1, f(2)=−3f(\sqrt{2}) = -3, f(3)=46f(3) = 46
    • Answer: Absolute maximum is 4646 at x=3x = 3; Absolute minimum is −3-3 at x=−2x = -\sqrt{2} and x=2x = \sqrt{2}.
  • Question 2: Find the absolute extrema of g(x)=x2x2+1g(x) = \frac{x^2}{x^2 + 1} on [−3,3][-3, 3].
    • Solution: g′(x)=2x(x2+1)−x2(2x)(x2+1)2=2x(x2+1)2=0  ⟹  x=0g'(x) = \frac{2x(x^2 + 1) - x^2(2x)}{(x^2 + 1)^2} = \frac{2x}{(x^2 + 1)^2} = 0 \implies x = 0
    • Evaluate candidates: g(−3)=9/10g(-3) = 9/10, g(0)=0g(0) = 0, g(3)=9/10g(3) = 9/10
    • Answer: Absolute maximum is 9/109/10 at x=±3x = \pm 3; Absolute minimum is 00 at x=0x = 0
  • Question 3: Find the absolute extrema of h(x)=cos⁡(x)−sin⁡(x)h(x) = \cos(x) - \sin(x) on [0,2π][0, 2\pi].
    • Solution: h′(x)=−sin⁡(x)−cos⁡(x)=0  ⟹  tan⁡(x)=−1  ⟹  x=3π/4,7π/4h'(x) = -\sin(x) - \cos(x) = 0 \implies \tan(x) = -1 \implies x = 3\pi/4, 7\pi/4
    • Evaluate candidates: h(0)=1h(0) = 1, h(3π/4)=−2h(3\pi/4) = -\sqrt{2}, h(7π/4)=2h(7\pi/4) = \sqrt{2}, h(2π)=1h(2\pi) = 1
    • Answer: Absolute maximum is 2\sqrt{2} at x=7π/4x = 7\pi/4; Absolute minimum is −21=−2\frac{-\sqrt{2}}{1} = -\sqrt{2} at x=3π/4x = 3\pi/4
  • Question 4: Practice logarithmic differentiation on the following expressions:
    • y=(x2+3)x  ⟹  ln⁡(y)=xln⁡(x2+3)  ⟹  y′=(x2+3)x[ln⁡(x2+3)+2x2x2+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−1)5x2+1(x+4)3  ⟹  y′=y[5x−1+xx2+1−3x+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=xcos⁡(x)  ⟹  y′=xcos⁡(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=(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]
  • Question 5: Prove that x5+x−3=0x^5 + x - 3 = 0 has a root in (1,2)(1, 2).
    • Solution: Let f(x)=x5+x−3f(x) = x^5 + x - 3. ff is continuous everywhere as a polynomial. f(1)=−1<0f(1) = -1 < 0 and f(2)=31>0f(2) = 31 > 0. By IVT, a root c∈(1,2)c \in (1, 2) exists.
  • Question 6: Prove that e−x=xe^{-x} = x has a solution in (0,1)(0, 1).
    • Solution: Let g(x)=e−x−xg(x) = e^{-x} - x. g(0)=1>0g(0) = 1 > 0 and g(1)=1/e−1<0g(1) = 1/e - 1 < 0. By IVT, g(c)=0  ⟹  e−c=cg(c) = 0 \implies e^{-c} = c for some c∈(0,1)c \in (0, 1).
  • Question 7: Perform two bisection steps for x3−4x+1=0x^3 - 4x + 1 = 0 starting on [0,1][0, 1].
    • Solution: f(x)=x3−4x+1f(x) = x^3 - 4x + 1. f(0)=1f(0) = 1, f(1)=−2f(1) = -2
    • Step 1: Midpoint m1=0.5m_1 = 0.5. f(0.5)=0.125−2+1=−0.875<0  ⟹  f(0.5) = 0.125 - 2 + 1 = -0.875 < 0 \implies new interval [0,0.5][0, 0.5]
    • Step 2: Midpoint m2=0.25m_2 = 0.25. f(0.25)=0.015625−1+1=0.015625>0  ⟹  f(0.25) = 0.015625 - 1 + 1 = 0.015625 > 0 \implies new interval [0.25,0.5][0.25, 0.5]
  • Question 8: Calculate how many bisection steps guarantee an interval length below 10−410^{-4} starting from [0,2][0, 2].
    • Solution: Initial length b−a=2b - a = 2. Need 22n<10−4  ⟹  2n−1>10000\frac{2}{2^n} < 10^{-4} \implies 2^{n - 1} > 10000. Since 213=81922^{13} = 8192 and 214=163842^{14} = 16384, set n−1=14  ⟹  n=15n - 1 = 14 \implies n = 15 steps.
  • Question 9: Analyze f(x)=x4−4x3+10f(x) = x^4 - 4x^3 + 10 completely.
    • Solution: f′(x)=4x3−12x2=4x2(x−3)=0  ⟹  x=0,3f'(x) = 4x^3 - 12x^2 = 4x^2(x - 3) = 0 \implies x = 0, 3
    • Decreasing on (−∞,0)∪(0,3)(-\infty, 0) \cup (0, 3); Increasing on (3,∞)(3, \infty)
    • x=0x = 0 is not an extremum (f′f' retains negative sign); Local minimum at x=3x = 3 with value f(3)=−17f(3) = -17
    • f′′(x)=12x2−24x=12x(x−2)=0  ⟹  x=0,2f''(x) = 12x^2 - 24x = 12x(x - 2) = 0 \implies x = 0, 2
    • Concave up on (−∞,0)∪(2,∞)(-\infty, 0) \cup (2, \infty); Concave down on (0,2)(0, 2)
    • Inflection points at (0,10)(0, 10) and (2,−6)(2, -6)
  • Question 10: Determine where f(x)=x4−4x2f(x) = x^4 - 4x^2 is convex or concave.
    • Solution: f′(x)=4x3−8x  ⟹  f′′(x)=12x2−8=4(3x2−2)f'(x) = 4x^3 - 8x \implies f''(x) = 12x^2 - 8 = 4(3x^2 - 2)
    • f′′(x)=0  ⟹  x=±2/3f''(x) = 0 \implies x = \pm\sqrt{2/3}
    • Convex (f′′≥0f'' \ge 0) on (−∞,−23]∪[23,∞)\left(-\infty, -\sqrt{\frac{2}{3}}\right] \cup \left[\sqrt{\frac{2}{3}}, \infty\right)
    • Concave (f′′<0f'' < 0) on (−23,23)\left(-\sqrt{\frac{2}{3}}, \sqrt{\frac{2}{3}}\right)