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Calc-1 Discussion 04

Discussion Topics covered: Rates of change and visual differentiability, computing derivatives from first principles via limit definition, power rule family, algebraic pre-processing and lowest-power post-processing, product rule, quotient rule, trigonometric derivatives, higher-order derivatives and tangent line linearization, logarithmic and exponential properties, decomposing composite functions, isolating target variables

Part A: Review This Week's Lecture Topics (~30 mins)

Rates of Change & Visual Differentiability

  • Distinguishing average rates of change (secant line slopes ΔyΔx=f(a+h)−f(a)h\frac{\Delta y}{\Delta x} = \frac{f(a+h)-f(a)}{h}) from instantaneous rates of change (tangent line slopes f′(a)=lim⁡h→0f(a+h)−f(a)hf'(a) = \lim_{h\to 0}\frac{f(a+h)-f(a)}{h})
  • Calculating derivatives on piecewise linear segments directly using the constant segment slope y2−y1x2−x1\frac{y_2 - y_1}{x_2 - x_1}
  • Diagnosing the four graphical failure modes of differentiability on coordinate curves: sharp corners, cusps, vertical tangents, and discontinuities
  • Proving differentiability implies continuity (differentiable  ⟹  continuous\text{differentiable} \implies \text{continuous}), and explaining why continuity is a necessary but not sufficient condition for differentiability (e.g., at sharp corners and cusps)

Computing Derivatives from Scratch via Limit Definition

  • Applying the limit definition of the difference quotient f′(x)=lim⁡h→0f(x+h)−f(x)hf'(x) = \lim_{h\to 0}\frac{f(x+h)-f(x)}{h} from first principles to resolve 00\frac{0}{0} indeterminate forms
  • Expanding polynomial difference quotients via binomial expansion ((x+h)2,(x+h)3(x+h)^2, (x+h)^3) and factoring out hh to cancel the denominator
  • Combining rational difference quotients over common denominators to clear compound fractions and isolate hh
  • Rationalizing radical difference quotients using radical conjugates (A+B)(\sqrt{A} + \sqrt{B}) and the difference of squares identity (a−b)(a+b)=a2−b2(a-b)(a+b) = a^2 - b^2 to release hh from under radicals

Fundamental Differentiation Rules & Exponent Pre/Post-Processing

  • Differentiating polynomials term-by-term using the Constant Rule (ddx[c]=0\frac{d}{dx}[c] = 0), Linear Identity Rule (ddx[x]=1\frac{d}{dx}[x] = 1), Constant Multiple Rule (ddx[cf(x)]=cf′(x)\frac{d}{dx}[c f(x)] = c f'(x)), Sum/Difference Rules, and Power Rule (ddx[xn]=nxn−1\frac{d}{dx}[x^n] = n x^{n-1})
  • Pre-processing expressions prior to differentiation: converting radicals to fractional powers (xmn→xmn\sqrt[n]{x^m} \to x^{\frac{m}{n}}) and lifting denominators to negative powers (cxn→cx−n\frac{c}{x^n} \to c x^{-n}) to bypass cumbersome quotient calculations
  • Avoiding the constant denominator trap by factoring out scalar denominators as constant coefficients (e.g., f(x)k=1kf(x)\frac{f(x)}{k} = \frac{1}{k}f(x)) rather than executing the Quotient Rule
  • Post-processing complex derivative results by factoring out the lowest (most negative) powers to yield clean factored expressions

Product, Quotient, and Trigonometric Derivative Rules

  • Applying the Product Rule ddx[uv]=u′v+uv′\frac{d}{dx}[uv] = u'v + uv' to multi-factor functions without committing the naive term-by-term multiplication error (ddx[uv]≠u′v′\frac{d}{dx}[uv] \neq u'v')
  • Applying the Quotient Rule ddx[uv]=u′v−uv′v2\frac{d}{dx}\left[\frac{u}{v}\right] = \frac{u'v - uv'}{v^2} ("Low dHigh minus High dLow over Low Low") and accurately distributing negative signs across numerator polynomial terms
  • Evaluating derivatives of all six fundamental trigonometric functions:
    ddx[sin⁡x]=cos⁡x,ddx[cos⁡x]=−sin⁡x,ddx[tan⁡x]=sec⁡2x\frac{d}{dx}[\sin x] = \cos x, \qquad \frac{d}{dx}[\cos x] = -\sin x, \qquad \frac{d}{dx}[\tan x] = \sec^2 x
    ddx[csc⁡x]=−csc⁡xcot⁡x,ddx[sec⁡x]=sec⁡xtan⁡x,ddx[cot⁡x]=−csc⁡2x\frac{d}{dx}[\csc x] = -\csc x \cot x, \qquad \frac{d}{dx}[\sec x] = \sec x \tan x, \qquad \frac{d}{dx}[\cot x] = -\csc^2 x

Higher-Order Derivatives & Tangent Line Linearization

  • Computing successive higher-order derivatives (f′′(x),f′′′(x),…,f(n)(x)f''(x), f'''(x), \dots, f^{(n)}(x)), exploiting polynomial termination when derivative order exceeds polynomial degree (k>n  ⟹  f(k)=0k > n \implies f^{(k)} = 0) and 4-step cyclic trigonometric periodicity (f(n)(x)=f(n mod 4)(x)f^{(n)}(x) = f^{(n \bmod 4)}(x))
  • Constructing tangent line equations using point-slope form y−f(a)=f′(a)(x−a)y - f(a) = f'(a)(x-a) from function formulas and discrete tabular sensor logs
  • Formulating linear approximations (linearizations) L(x)=f(a)+f′(a)(x−a)L(x) = f(a) + f'(a)(x-a) for local physical system estimation

Part B: Next Week's Prerequisite Refresher (~30 mins)

Review the following prerequisite skills:

Part C: General Q/A

Open the floor to questions from students regarding any topic