Unit 4 · 22 min read
Applications of Derivatives
What the syllabus asks for 8
- Tangent and normal
- Rates of change and related rates
- Increasing, decreasing, maxima and minima
- Optimisation
- Mean value theorems
- L'Hôpital's rule
- Taylor and Maclaurin series
- Eight uses of the applications of derivatives
Derivatives are used to describe tangents, rates, optimum values and approximations.
This unit turns the differentiation rules of Unit 3 into tools for solving problems: tangent lines, related rates, maxima and minima, the mean value theorems, L'Hôpital's rule and Taylor/Maclaurin series.
- Tangent and normal lines; rates of change and related rates.
- Increasing/decreasing functions, maxima and minima, optimisation, concavity.
- Rolle's theorem, the mean value theorem, L'Hôpital's rule.
- Maclaurin and Taylor series, with numerical approximation.
4.1 Tangent and normal
The tangent to y = f (x) at (a ,\ f (a)) has slope m = f' (a): y - f (a) = f' (a) (x - a). The normal is perpendicular, with slope - \frac{1}{f' (a)} (if f' (a) \neq 0).
For y = x^{3} - 2 x + 1 at x = 1: y (1) = 0 and y' = 3 x^{2} - 2 = 1. Tangent: y = x - 1. Normal: slope −1, so y = - (x - 1) = 1 - x.
4.2 Rates of change and related rates
\frac{d y}{d x} is the rate of change of y with respect to x. For a position function s (t): velocity v = \frac{d s}{d t}, acceleration a = \frac{d v}{d t} = \frac{d^{2} s}{d t^{2}}.
Related rates: two quantities are tied by an equation; differentiate it with respect to time.
A 10 m ladder leans on a wall; the foot slides away at 2 \frac{m}{s}.
How fast does the top fall when the foot is 6 m from the wall? x^{2} + y^{2} = 100 \Rightarrow 2 x x' + 2 y y' = 0 \Rightarrow y' = - \left( \frac{x}{y} \right) x'.
When x = 6 ,\ y = 8, so y' = - \left( \frac{6}{8} \right) (2) = - \frac{1.5 m}{s} (the top slides down at 1.5 \frac{m}{s}).
The radius of a circular oil slick grows at 3 cm/s. At r = 10 cm, \dfrac{dA}{dt} = 2\pi r\,\dfrac{dr}{dt} = 2\pi (10)(3) = \mathbf{60\pi \approx 188.5\ \mathrm{cm^{2}/s}}.
4.3 Increasing, decreasing, maxima and minima
- f' (x) > 0 on an interval ⇒ f increasing; f' (x) < 0 ⇒ decreasing.
- A critical point is where f' (x) = 0 or f' does not exist. Local maxima and minima occur only at critical points.
- First-derivative test: f' changes + to − ⇒ local max; − to + ⇒ local min; no change ⇒ neither.
- Second-derivative test: at f' (c) = 0, if f'' (c) > 0 then local min; f'' (c) < 0 ⇒ local max; f'' (c) = 0 ⇒ test fails.
- Concavity: f'' > 0 concave up (holds water); f'' < 0 concave down. A point of inflection is where concavity changes (f'' = 0 and changes sign).
- On a closed interval [a ,\ b] the absolute extremes occur at critical points or the endpoints, so compare all candidates.
f (x) = x^{3} - 6 x^{2} + 9 x + 1. f' = 3 x^{2} - 12 x + 9 = 3 (x - 1) (x - 3). f'' = 6 x - 12.
At x = 1: f'' = - 6 < 0, local maximum, f (1) = 5. At x = 3: f'' = 6 > 0, local minimum, f (3) = 1. Inflection at f'' = 0 ,\ x = 2 ,\ f (2) = 3. f is increasing on (- \infty, 1) and (3 ,\ \infty), decreasing on (1, 3).
On [0, 4]: f (0) = 1 ,\ f (1) = 5 ,\ f (3) = 1 ,\ f (4) = 5. Absolute max 5 (at x = 1 and x = 4), absolute min 1 (at x = 0 and x = 3).
4.4 Optimisation
Steps: (1) draw and name variables; (2) write the quantity to optimise; (3) use the constraint to reduce it to one variable; (4) find critical points and test; (5) answer the question asked, with units.
From a 12 cm × 12 cm square, cut equal squares of side x from the corners and fold up an open box. V = x (12 - 2 x)^{2} for 0 < x < 6. V' = (12 - 2 x)^{2} - 4 x (12 - 2 x) = (12 - 2 x) (12 - 6 x) = 0 \Rightarrow x = 2 ( x = 6 gives V = 0). V'' at x = 2 is negative (V' goes + to −), so maximum V = 2 \times 8^{2} = 128 \mathrm{cm}^{3}.
A rectangle has perimeter 40 m. Width w, length 20 - w ;\ A = w (20 - w) ,\ A' = 20 − 2w = 0 \Rightarrow w = 10 ,\ A'' = - 2 < 0. Maximum area 100 m^{2}, a square.
A closed cylindrical can must hold 500 \mathrm{cm}^{3}.
Minimise surface area S = 2 \pi r^{2} + 2 \pi r h with h = \frac{500}{(\pi r^{2})}: S = 2 \pi r^{2} + \frac{1000}{r}. S' = 4 \pi r - \frac{1000}{r^{2}} = 0 \Rightarrow r^{3} = \frac{250}{\pi} ,\ r \approx 4.30 cm, h = 2r ≈ 8.60 cm.
The best can has height equal to its diameter.
4.5 Mean value theorems
Rolle's theorem. If f is continuous on [a ,\ b], differentiable on (a ,\ b) and f (a) = f (b), then f' (c) = 0 for some c in (a ,\ b).
Mean value theorem (MVT). If f is continuous on [a ,\ b] and differentiable on (a ,\ b), there is c in (a ,\ b) with f' (c) = \frac{f (b) - f (a)}{b - a}, a tangent parallel to the chord.
Rolle: f (x) = x^{2} - 4 x + 3 on [1, 3]: f (1) = f (3) = 0 ;\ f' (x) = 2 x - 4 = 0 at c = 2, inside the interval ✓.
MVT: f (x) = x^{3} on [0, 2]: slope of chord = \frac{8 - 0}{2} = 4.
Set f' (c) = 3 c^{2} = 4, so c = \frac{2}{\sqrt{3}} \approx 1.155, which lies in (0, 2) ✓.
Use: MVT proves that if f' = 0 on an interval then f is constant, and gives inequalities such as |\sin a - \sin b| \le |a - b|.
4.6 L'Hôpital's rule
If \lim \frac{f}{g} gives \frac{0}{0} or \frac{\infty}{\infty} and \lim \frac{f'}{g'} exists (or is \pm \infty), then \lim \frac{f}{g} = \lim \frac{f'}{g'}. It can be applied repeatedly.
Other forms (0 \cdot \infty ,\ \infty - \infty ,\ 1^{\infty} ,\ 0^{0} ,\ \infty^{0}) are first rewritten as a quotient, using ln for exponent forms.
(a) \lim_{x \to 0} \frac{e^{x} - 1 - x}{x^{2}}: \frac{0}{0} \to \frac{e^{x} - 1}{2 x}: \frac{0}{0} \to \frac{e^{x}}{2} → \frac{1}{2}.
(b) \lim_{x \to 0} \frac{\sin x - x}{x^{3}} \to \frac{\cos x - 1}{(3 x^{2})} \to \frac{- \sin x}{6 x} \to \frac{- \cos x}{6} → - \frac{1}{6}.
(c) \lim_{x \to 0^{+}} x \ln x = \lim \frac{\ln x}{\frac{1}{x}} = \lim \frac{\frac{1}{x}}{- \frac{1}{x^{2}}} = \lim (- x) = 0.
(d) \lim_{x \to 0^{+}} x^{x}: \ln y = x \ln x \to 0, so y \to e^{0} = 1.
(e) \lim_{x \to \infty} \frac{\ln x}{x}: \frac{\infty}{\infty} \to \frac{1/x}{1} → 0. A logarithm grows slower than any power.
(f) \lim_{x \to \infty} \left(1 + \frac{1}{x}\right)^{x} has the form 1^{\infty}.
Put y = \left(1 + \frac{1}{x}\right)^{x}, so \ln y = \frac{\ln(1 + 1/x)}{1/x}, which is \frac{0}{0}.
Differentiate top and bottom: the top gives \frac{-1/x^{2}}{1 + 1/x}, the bottom gives -\frac{1}{x^{2}}, so \ln y \to \frac{1}{1 + 1/x} \to 1.
Hence y \to e^{1} = e.
4.7 Taylor and Maclaurin series
If f has derivatives of all orders at a, its Taylor series is
With a = 0 it is the Maclaurin series. The first n terms form a polynomial approximation, the remainder is the error.
| Function | Maclaurin series | Valid for |
|---|---|---|
| e^{x} | 1 + x + \frac{x^{2}}{2 !} + \frac{x^{3}}{3 !} + \ldots | all x |
| \sin x | x - \frac{x^{3}}{3 !} + \frac{x^{5}}{5 !} - \ldots | all x |
| \cos x | 1 - \frac{x^{2}}{2 !} + \frac{x^{4}}{4 !} - \ldots | all x |
| \ln (1 + x) | x - \frac{x^{2}}{2} + \frac{x^{3}}{3} - \ldots | - 1 < x \leq 1 |
| \frac{1}{1 - x} | 1 + x + x^{2} + x^{3} + \ldots | |x| < 1 |
| (1 + x)^{n} | 1 + n x + \frac{n (n - 1) x^{2}}{2 !} + \ldots | |x| < 1 |
\sin (0.1) \approx 0.1 - \frac{(0.1)^{3}}{6} = 0.1 - 0.000167 = 0.099833 (true value 0.0998334). \sqrt{1.02} = (1 + 0.02)^{\frac{1}{2}} \approx 1 + 0.01 - 0.00005 = 1.00995. Also e^{0.2} \approx 1 + 0.2 + 0.02 + 0.001333 + 0.0000667 = 1.221400 (true 1.221403).
Linear approximation (differentials). f (x + \Delta x) \approx f (x) + f' (x) \Delta x. For ∛8.1: f (x) = x^{\frac{1}{3}} ,\ f' (8) = \frac{1}{12}, so ∛8.1 ≈ 2 + 0.1 / 12 = 2.00833.

4.8 Eight uses of the applications of derivatives
- Cheapest and strongest designs. Engineers minimise material for a fixed volume, as in the can of Figure 4.2. A ghee or soft-drink company saves thousands of rupees of metal by using the best radius-to-height ratio. The same method is used for tanks, pipes and packaging.
- Maximum profit and revenue. If the price per ticket falls, more people buy, so revenue is price × number and has a maximum. Setting the derivative to zero finds the best price. Cinema halls in Kathmandu and bus companies use the idea when setting fares.
- Related rates in construction and water supply. The ladder problem (Figure 4.1) shows how one moving distance forces others to change. The same chain-rule thinking tells how fast the level in a tank rises while it is filled. It is needed for safe design of dams and reservoirs.
- Speeding cars and safety. Speed is the derivative of position, and the Mean Value Theorem (Figure 4.3) guarantees that a car covering 120 km in 2 hours was going exactly 60 km/h at some moment. Highway cameras in some countries use average speed over a stretch for this reason. It is a simple proof from calculus.
- Curve sketching and graph reading. The first derivative shows where a function rises, falls or turns, and the second shows how it bends. Data analysts use this to find peaks in sales, demand or website traffic. Software draws a good graph automatically in the same way.
- Finding roots with Newton's method. To solve f (x) = 0 start from a guess x_{0} and repeat x_{1} = x_{0} - \frac{f (x_{0})}{f' (x_{0})}. Each step uses the tangent line, and the sequence converges very fast. Calculators and computers find square roots this way.
- Indeterminate limits by L'Hôpital's rule. When a limit is \frac{0}{0} or \frac{\infty}{\infty} we can differentiate the top and bottom separately. For example \lim_{x \to 0} \frac{e^{x} - 1 - x}{x^{2}} = \frac{1}{2}. This saves long algebra in examination problems and in algorithm analysis.
- Approximation by Taylor series. Calculators compute \sin x ,\ \cos x and e^{x} by adding the first few terms of a Maclaurin series (Plate 4.1). The error is small because the terms shrink quickly. Without Taylor series, computers could not evaluate these functions at all.

Formula and fact sheet
- Tangent at a: y - f (a) = f' (a) (x - a); normal slope - \frac{1}{f' (a)}.
- Critical point: f' = 0 or undefined. f'' > 0 min, f'' < 0 max.
- MVT: f' (c) = \frac{f (b) - f(a) }{b - a}; Rolle is the case f (a) = f(b) .
- L'Hôpital: \frac{0}{0} or \frac{\infty}{\infty} → differentiate top and bottom separately.
- Maclaurin: e^{x} ,\ \sin x ,\ \cos x ,\ \ln (1 + x) ,\ (1 + x)^{n} as in the table.
- Related rates: write the relation, differentiate with respect to t, substitute.
Chapter summary
- The derivative gives tangents, rates, and the shape of a graph (increasing, decreasing, concave).
- Optimisation reduces a real problem to one variable and tests critical points and endpoints.
- Rolle and the MVT link the average slope to an instantaneous slope; L'Hôpital turns indeterminate limits into derivative quotients.
- Taylor series replace a function by polynomials and enable numerical approximation.
Practice
- Find the tangent and normal to y = x^{2} - 3 x + 2 at x = 2.
- A balloon's radius grows at 2 cm/s. Find the rate at which its volume grows when r = 5 cm.
- Find the local extrema and inflection point of f (x) = 2 x^{3} - 9 x^{2} + 12 x.
- Find the dimensions of the rectangle of maximum area inscribed in a circle of radius R.
- A farmer has 200 m of fence for a rectangular pen against a river wall (no fence along the river). Find the maximum area.
- Verify the MVT for f (x) = x^{2} on [1, 3].
- Evaluatea\lim_{x \to 0} \frac{e^{x} - e^{- x}}{\sin x},b\lim_{x \to 0} \frac{\tan x - x}{x^{3}},c\lim_{x \to 0} (\cos x)^{\frac{1}{x^{2}}}.
- Write the Maclaurin series of \cos x up to x^{4} and use it to estimate \cos (0.2).
- Use a linear approximation for \sqrt{26}.
- Show that x - \frac{x^{2}}{2} < \ln (1 + x) < x for x > 0.
Answers and worked solutions
1. y (2) = 0 ,\ y' = 2 x - 3 = 1. Tangent y = x - 2; normal y = - (x - 2) = 2 - x.
2. V = \left( \frac{4}{3} \right) \pi r^{3}, \dfrac{dV}{dt} = 4\pi r^{2}\,\dfrac{dr}{dt} = 4\pi \cdot 25 \cdot 2 = \mathbf{200\pi \approx 628.3\ \mathrm{cm^{3}/s}}.
3. f' = 6 x^{2} - 18 x + 12 = 6 (x - 1) (x - 2) ;\ f'' = 12 x - 18. x = 1: f'' = - 6, max f (1) = 5. x = 2: f'' = 6, min f (2) = 4. Inflection at x = 1.5 ,\ f (1.5) = 4.5.
4. With sides x and y ,\ x^{2} + y^{2} = 4 R^{2} and A = x y. Maximising A^{2} = x^{2} (4 R^{2} - x^{2}) gives x^{2} = 2 R^{2}, so x = y = R \sqrt{2}: a square of area 2 R^{2}.
5. Width w (two sides), length 200 − 2w: A = w ( 200 − 2w), A' = 200 − 4w = 0 \Rightarrow w = 50, length 100, A = 5000 m^{2}.
6. Chord slope (9 - 1 ) / 2 = 4 ;\ f' (c) = 2 c = 4 \Rightarrow c = 2 \in ( 1, 3) ✓.
7.(a) \frac{0}{0} \to \frac{e^{x} + e^{- x}}{\cos x} → 2.(b) → \frac{\sec^{2} x - 1}{(3 x^{2})} = \frac{\tan^{2} x}{(3 x^{2})} → \frac{1}{3}.(c) \ln y = \frac{\ln \cos x}{x^{2}} \to \frac{- \tan x}{2 x} → - \frac{1}{2}, so the limit is e^{- \frac{1}{2}}.
8. \cos x \approx 1 - \frac{x^{2}}{2} + \frac{x^{4}}{24} ;\ \cos 0.2 \approx 1 - 0.02 + 0.0000667 = 0.980067 (true 0.980067).
9. f (x) = \sqrt{x} at 25: f' = 1/(2·5) = 0.1 ;\ \sqrt{26} \approx 5 + 0.1 = 5.1 (true 5.0990).
10. Let g (x) = \ln (1 + x) - x + \frac{x^{2}}{2}. g (0) = 0 and g' = \frac{1}{1 + x} - 1 + x = \frac{x^{2}}{1 + x} > 0, so g > 0 for x > 0. Let h (x) = x - \ln (1 + x) ;\ h (0) = 0 ,\ h' = \frac{x}{1 + x} > 0, so h > 0. ∎
Model answers: medium (5 marks) and long (10 marks) questions
Q (5 marks). Find the local maximum and minimum values of f (x) = 2 x^{3} - 9 x^{2} + 12 x + 1 and say where the function is increasing.
A local extreme can occur only at a critical point, where f' (x) = 0 (or f' does not exist). The second derivative test then decides: f'' < 0 gives a local maximum and f'' > 0 a local minimum.
- Differentiate: f' (x) = 6 x^{2} - 18 x + 12 = 6 (x^{2} - 3 x + 2) = 6 (x - 1) (x - 2).
- Critical points: f' = 0 gives x = 1 and x = 2.
- Second derivative: f'' (x) = 12 x - 18. At x = 1 ,\ f'' = - 6 < 0, so x = 1 is a local maximum. At x = 2 ,\ f'' = 6 > 0, so x = 2 is a local minimum.
- Values: f (1) = 2 - 9 + 12 + 1 = 6 (maximum) and f (2) = 16 - 36 + 24 + 1 = 5 (minimum).
- Sign of f': positive for x < 1, negative for 1 < x < 2, positive for x > 2.
| Interval | x < 1 | 1 < x < 2 | x > 2 |
|---|---|---|---|
| f' (x) | + | − | + |
| f | increasing | decreasing | increasing |
So f is increasing on (- \infty, 1) and (2 ,\ \infty) and decreasing on (1, 2). The "maximum" 6 is only local: the cubic has no global maximum, because f \to \infty as x \to \infty.
Q (5 marks). Write the Maclaurin series of e^{x} up to the term in x^{4} and use it to estimate e^{0} . 5. Find the error.
The Maclaurin series of f is f (0) + f' (0) x + \frac{f'' (0) x^{2}}{2 !} + \frac{f''' (0) x^{3}}{3 !} + \ldots, the Taylor series about 0 (Plate 4.1).
- For f (x) = e^{x} every derivative is e^{x}, so every derivative at 0 equals 1.
- Therefore e^{x} = 1 + x + \frac{x^{2}}{2 !} + \frac{x^{3}}{3 !} + \frac{x^{4}}{4 !} + \ldots
- Put x = 0.5: 1 + 0.5 + 0.125 + 0.5^{3} / 6 + 0.5^{4} / 24 = 1 + 0.5 + 0.125 + 0.020833 + 0.002604.
- The sum is 1.648438.
- The true value is e^{0} . 5 = 1.648721, so the error is about 0.00028, less than the first omitted term \frac{x^{5}}{5 !} = 0.000260 (plus smaller ones).
Conclusion: four terms give three correct decimals. More terms give more accuracy, and for small |x| the series converges very fast, which is how calculators evaluate e^{x}.
Q (10 marks). State the Mean Value Theorem with its geometrical meaning and verify it for f (x) = x^{3} on [0, 2]. Explain the steps of an optimisation problem with the example of a closed can of volume 1000 \mathrm{cm}^{3}, and state L'Hôpital's rule with an example.
Introduction. The derivative tells how a function changes, so it can describe, estimate and optimise real systems. Three results of this unit are the Mean Value Theorem, optimisation and L'Hôpital's rule.
Mean Value Theorem (MVT). If f is continuous on [a ,\ b] and differentiable on (a ,\ b), there is at least one c in (a ,\ b) with f' (c) = \frac{f (b) - f (a)}{b - a}.
Geometrically some tangent is parallel to the secant joining the end points (Figure 4.3).
Verification for f (x) = x^{3} on [0, 2] the secant slope is \frac{8 - 0}{2} = 4. Solve f' (c) = 3 c^{2} = 4, so c = \frac{2}{\sqrt{3}} \approx 1.155, which lies in (0, 2). ✓ Rolle's theorem is the special case f (a) = f (b), where f' (c) = 0.
Optimisation steps (Figure 4.2).
- Draw a picture and name the variables (radius r, height h).
- Write the quantity to optimise: S = 2 \pi r^{2} + 2 \pi r h.
- Use the constraint V = \pi r^{2} h = 1000 to remove h: S (r) = 2 \pi r^{2} + \frac{2000}{r}.
- Differentiate and solve S' (r) = 4 \pi r - \frac{2000}{r^{2}} = 0, giving r^{3} = \frac{500}{\pi}, so r \approx 5.42 cm.
- Check it is a minimum: S'' = 4 \pi + \frac{4000}{r^{3}} > 0.
- State the answer: h = \frac{1000}{(\pi r^{2})} \approx 10.84 cm = 2r, and S ≈ 553.6 \mathrm{cm}^{2}. The best can has height equal to its diameter.
L'Hôpital's rule. If \lim \frac{f}{g} has the form \frac{0}{0} or \frac{\infty}{\infty}, then \lim \frac{f}{g} = \lim \frac{f'}{g'} provided the latter exists.
Example \lim_{x \to 0} \frac{x - \sin x}{x^{3}} is \frac{0}{0}; differentiating gives \frac{1 - \cos x}{(3 x^{2})}, still \frac{0}{0}; again gives \frac{\sin x}{6 x} → \frac{1}{6}.
Another \lim_{x \to \infty} \frac{\ln x}{x} is \frac{\infty}{\infty} and equals \lim \frac{\frac{1}{x}}{1} = 0, so logarithms grow slower than any power.
Comparison of the three tools.
| Tool | Needs | Gives |
|---|---|---|
| MVT | continuity on [a ,\ b], differentiable inside | a point where the slope equals the average slope |
| Optimisation | a function of one variable | the best \left( \frac{\max}{\min} \right) value |
| L'Hôpital | an indeterminate form \frac{0}{0} or \frac{\infty}{\infty} | the value of the limit |
Conclusion. The derivative is a practical tool: it finds the cheapest can, proves facts about speed, and evaluates difficult limits. These three results are the standard long questions of this unit.