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Chapter 7

Applications of Differential Calculus

Mean value theorem, series expansions, optimization and curve sketching.

1. The derivative as slope and rate of change

The derivative f(x)f'(x) measures how fast a function changes. Geometrically it is the slope of the tangent line to the curve y=f(x)y = f(x) at each point. Physically, if s(t)s(t) is position, then s(t)s'(t) is velocity — an instantaneous rate of change.

DefinitionDerivative at a point

f(a)=limh0f(a+h)f(a)hf'(a) = \displaystyle\lim_{h \to 0} \dfrac{f(a+h) - f(a)}{h}, the limit of average rates of change over shorter and shorter intervals.

Key idea: The sign of $f'(a)$ tells you the direction of motion of the curve: rising if positive, falling if negative, flat if zero. Explore this live in the Visualize tab.

2. Tangent and normal lines

At the point (a,f(a))(a, f(a)) the tangent has slope m=f(a)m = f'(a). The normal is perpendicular to the tangent, so its slope is 1f(a)-\dfrac{1}{f'(a)} (when f(a)0f'(a) \neq 0).

Tangent at (a, f(a))
yf(a)=f(a)(xa)y - f(a) = f'(a)\,(x - a)
Normal at (a, f(a))
yf(a)=1f(a)(xa)y - f(a) = -\dfrac{1}{f'(a)}\,(x - a)
ExampleTangent to a curve
Find the equation of the tangent to y=x2y = x^2 at the point (2,4)(2, 4).
ExampleNormal line
Find the normal to y=x2y = x^2 at (2,4)(2, 4).

3. Mean Value Theorems

These theorems connect a function's overall behaviour on an interval to its derivative at some point inside. They underpin much of calculus.

DefinitionRolle's Theorem

If ff is continuous on [a,b][a, b], differentiable on (a,b)(a, b), and f(a)=f(b)f(a) = f(b), then there exists c(a,b)c \in (a, b) with f(c)=0f'(c) = 0.

DefinitionLagrange's Mean Value Theorem

If ff is continuous on [a,b][a, b] and differentiable on (a,b)(a, b), then there exists c(a,b)c \in (a, b) with f(c)=f(b)f(a)baf'(c) = \dfrac{f(b) - f(a)}{b - a}.

Note: Lagrange's MVT says: somewhere inside the interval, the instantaneous slope equals the average slope of the chord from $(a, f(a))$ to $(b, f(b))$. Rolle's is the special case where the chord is horizontal.
ExampleApplying Rolle's theorem
Verify Rolle's theorem for f(x)=x24x+3f(x) = x^2 - 4x + 3 on [1,3][1, 3] and find cc.

4. Taylor and Maclaurin series

A smooth function can be approximated near a point by a polynomial built from its derivatives. The Taylor series expands about x=ax = a; the Maclaurin series is the special case a=0a = 0.

Taylor series about x = a
f(x)=f(a)+f(a)(xa)+f(a)2!(xa)2+f(a)3!(xa)3+f(x) = f(a) + f'(a)(x-a) + \dfrac{f''(a)}{2!}(x-a)^2 + \dfrac{f'''(a)}{3!}(x-a)^3 + \cdots
Maclaurin series (a = 0)
f(x)=f(0)+f(0)x+f(0)2!x2+f(0)3!x3+f(x) = f(0) + f'(0)\,x + \dfrac{f''(0)}{2!}x^2 + \dfrac{f'''(0)}{3!}x^3 + \cdots
Standard Maclaurin expansions
  • ex=1+x+x22!+x33!+e^x = 1 + x + \dfrac{x^2}{2!} + \dfrac{x^3}{3!} + \cdots
  • sinx=xx33!+x55!\sin x = x - \dfrac{x^3}{3!} + \dfrac{x^5}{5!} - \cdots
  • cosx=1x22!+x44!\cos x = 1 - \dfrac{x^2}{2!} + \dfrac{x^4}{4!} - \cdots
  • log(1+x)=xx22+x33\log(1 + x) = x - \dfrac{x^2}{2} + \dfrac{x^3}{3} - \cdots (for x<1|x| < 1)
ExampleDeriving a series
Find the first three non-zero terms of the Maclaurin series of cosx\cos x.

5. Indeterminate forms and L'Hôpital's Rule

When a limit gives a meaningless form such as 00\dfrac{0}{0} or \dfrac{\infty}{\infty}, you cannot read off the answer directly. L'Hôpital's rule replaces the ratio by the ratio of derivatives.

DefinitionL'Hôpital's Rule

If limxaf(x)g(x)\displaystyle\lim_{x \to a} \dfrac{f(x)}{g(x)} has the form 00\dfrac{0}{0} or \dfrac{\infty}{\infty}, then limxaf(x)g(x)=limxaf(x)g(x)\displaystyle\lim_{x \to a} \dfrac{f(x)}{g(x)} = \lim_{x \to a} \dfrac{f'(x)}{g'(x)}, provided the second limit exists.

Watch out: Check the indeterminate form first. Applying L'Hôpital to a limit that is not $\dfrac{0}{0}$ or $\dfrac{\infty}{\infty}$ gives wrong answers. Forms like $0 \cdot \infty$ or $\infty - \infty$ must first be rewritten as a quotient.
ExampleA 0/0 limit
Evaluate limx0sinxx\displaystyle\lim_{x \to 0} \dfrac{\sin x}{x}.

6. Increasing, decreasing and stationary points

The first derivative reveals where a function rises or falls. Where f(x)=0f'(x) = 0 (or is undefined) the curve momentarily levels off — a stationary point.

  • f(x)>0f'(x) > 0 on an interval \Rightarrow ff is increasing there.
  • f(x)<0f'(x) < 0 on an interval \Rightarrow ff is decreasing there.
  • f(x)=0f'(x) = 0 \Rightarrow a stationary point (candidate max, min, or inflection).
ExampleIntervals of increase
Find where f(x)=x33xf(x) = x^3 - 3x is increasing.

7. Maxima and minima

At a stationary point you decide whether it is a peak, a valley, or neither using one of two tests.

First-derivative test at a stationary point x = c
  • ff' changes ++ \to - across cc: local maximum.
  • ff' changes +- \to + across cc: local minimum.
  • ff' does not change sign: neither (a point of inflection).
Second-derivative test at a stationary point
f(c)=0, f(c)<0local max;f(c)=0, f(c)>0local minf'(c) = 0,\ f''(c) < 0 \Rightarrow \text{local max}; \qquad f'(c) = 0,\ f''(c) > 0 \Rightarrow \text{local min}
Note: If $f''(c) = 0$ the second-derivative test is inconclusive; fall back on the first-derivative test.
ExampleLocal max and min of a cubic
Find the local maximum and minimum values of f(x)=x33xf(x) = x^3 - 3x.
ExampleOptimization word problem
A rectangular field is fenced with 100100 m of fencing. What dimensions give the maximum area?

8. Concavity, inflection, asymptotes and curve sketching

The second derivative controls how the curve bends. Where it changes sign, the concavity flips — a point of inflection.

  • f(x)>0f''(x) > 0: curve is concave up (holds water).
  • f(x)<0f''(x) < 0: curve is concave down.
  • f(x)=0f''(x) = 0 with a sign change: point of inflection.
DefinitionAsymptotes

A vertical asymptote occurs where f±f \to \pm\infty (e.g. x=2x = 2 for 1x2\dfrac{1}{x-2}). A horizontal asymptote y=Ly = L occurs when limx±f(x)=L\displaystyle\lim_{x \to \pm\infty} f(x) = L.

Curve-sketching checklist
  • Domain, intercepts, and symmetry.
  • Stationary points and their nature (first/second derivative test).
  • Intervals of increase/decrease and concavity; points of inflection.
  • Asymptotes and end behaviour as x±x \to \pm\infty.