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Application of Derivatives

Use derivatives to study rate of change, increasing and decreasing functions, tangents and normals, and maxima and minima, with classic optimization problems.

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Reading time~11 min
Revision time~4 min
Last updated2026-07-17
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🎯 Key Points

  • f'(x)>0 → strictly increasing; f'(x)<0 → strictly decreasing; f'(x)=0 throughout → constant
  • First Derivative Test: sign change +→- at c means local MAX; -→+ means local MIN; no sign change means inflection (neither)
  • Linear approximation: f(x+Δx) ≈ f(x)+f'(x)·Δx — the basis for quickly estimating √25.2, cube roots, etc. near a known value
  • Absolute extrema on [a,b]: check ALL critical points INSIDE (a,b) AND both endpoints a, b — missing the endpoints is a common error since the true global max/min can occur there even if f' never vanishes there
  • Rolle's theorem (f(a)=f(b) case) is a SPECIAL CASE of the Mean Value Theorem (general case) — MVT's conclusion reduces to Rolle's when the right side [f(b)-f(a)]/(b-a) becomes 0
Tangent and Normal at a Point on a Curve(a,b)tangent (slope=f'(a))normal (slope=-1/f'(a))Tangent and normal are always perpendicular to each other at the point of contact

The tangent at a point touches the curve with slope f'(a); the normal is the line perpendicular to the tangent at that same point, with slope -1/f'(a) — together they describe the curve's local direction and the line "straight into" the curve.

Application of Derivatives

Derivatives are not just abstract formulas, they have powerful real-world and geometric applications. This chapter uses the derivative as a rate of change and as a tool to study the shape and behavior of curves, find tangents and normals, locate maximum and minimum values, and solve optimization problems.

Rate of Change of Quantities

  • If y = f(x), the derivative dy/dx represents the instantaneous rate of change of y with respect to x.
  • If two quantities x and y are both functions of time t, and are related, then dy/dt = (dy/dx) × (dx/dt) (chain rule), which is the basis of "related rates" problems.
  • Example: For a circle, Area A = πr². Then dA/dt = 2πr × dr/dt, relating the rate of change of area to the rate of change of radius.
  • Example: For a sphere, Volume V = (4/3)πr³. Then dV/dt = 4πr² × dr/dt.

Increasing and Decreasing Functions

  • A function f is strictly increasing on an interval if f'(x) > 0 for all x in that interval.
  • A function f is strictly decreasing on an interval if f'(x) < 0 for all x in that interval.
  • If f'(x) = 0 throughout an interval, f is constant there.
  • Method: Find f'(x), set f'(x) = 0 to get critical points, then test the sign of f'(x) in each interval formed by these points on the number line.

Tangents and Normals

  • The slope of the tangent to y = f(x) at point (x₁, y₁) is m = f'(x₁), the derivative evaluated at that point.
  • Equation of tangent: y - y₁ = f'(x₁)(x - x₁)
  • The normal is perpendicular to the tangent at the point of contact, so its slope is -1/f'(x₁) (when f'(x₁) ≠ 0).
  • Equation of normal: y - y₁ = -1/f'(x₁) × (x - x₁)
  • If f'(x₁) = 0, the tangent is horizontal (parallel to the x-axis) and the normal is vertical (x = x₁).
  • If f'(x₁) is undefined (tangent vertical), the tangent is x = x₁ and the normal is horizontal.

Approximations Using Derivatives

  • For a small change Δx in x, the corresponding small change in y is approximated as Δy ≈ f'(x) × Δx.
  • This gives the approximation f(x + Δx) ≈ f(x) + f'(x) × Δx, useful for estimating values like square roots or cube roots near a known point.
  • Example: To approximate √25.2, take f(x) = √x, x = 25, Δx = 0.2. Then f'(x) = 1/(2√x) = 1/10, so √25.2 ≈ 5 + 0.1 × 0.2 = 5.02.

Maxima and Minima

  • Critical point: A point c in the domain where f'(c) = 0 or f'(c) does not exist.
  • Local maximum: f(c) is greater than or equal to f(x) for all x in some neighborhood of c.
  • Local minimum: f(c) is less than or equal to f(x) for all x in some neighborhood of c.
  • First Derivative Test: At a critical point c, if f'(x) changes sign from positive to negative as x increases through c, f has a local maximum at c. If it changes from negative to positive, f has a local minimum. If there is no sign change, c is a point of inflection (neither maximum nor minimum).
  • Second Derivative Test: At a critical point c where f'(c) = 0: if f''(c) < 0, f has a local maximum at c. If f''(c) > 0, f has a local minimum at c. If f''(c) = 0, the test fails and the first derivative test must be used.
  • Absolute (global) maximum/minimum: On a closed interval [a, b], the absolute extrema occur either at critical points inside (a, b) or at the endpoints a and b. Evaluate f at all of these and compare.

Curve Sketching Basics

  • Find intervals of increase and decrease using f'(x).
  • Locate local maxima and minima using the first or second derivative test.
  • Find points of inflection where f''(x) = 0 and concavity changes (concave up when f''(x) > 0, concave down when f''(x) < 0).
  • Combine this information with intercepts and asymptotes to sketch the general shape of the curve.

Optimization Word Problems

  • General method: write the quantity to be maximized/minimized as a function of one variable using the given constraint, differentiate, set the derivative to zero, and apply the second derivative test to confirm a maximum or minimum.
  • Classic example (maximum area): Among all rectangles with a fixed perimeter, the square encloses the maximum area. If x + y = 20, area A = xy = x(20 - x) is maximized at x = y = 10, giving maximum area 100.
  • Classic example (minimum cost/material): Among all closed cylinders of a given volume, the one with height equal to the diameter (h = 2r) has minimum surface area.
  • Classic example (maximum volume box): Cutting equal squares of side x from the corners of a square sheet of side a and folding up the sides gives an open box of volume V = x(a - 2x)², maximized at x = a/6.

Rolle's Theorem and Mean Value Theorem

  • Rolle's Theorem: If f is continuous on [a, b], differentiable on (a, b), and f(a) = f(b), then there exists at least one point c in (a, b) such that f'(c) = 0.
  • Geometric meaning: somewhere between two points of equal height on the curve, the tangent must be horizontal.
  • Lagrange's Mean Value Theorem (MVT): If f is continuous on [a, b] and differentiable on (a, b), then there exists at least one point c in (a, b) such that f'(c) = [f(b) - f(a)] / (b - a).
  • Geometric meaning: there is some point on the curve where the tangent is parallel to the chord joining (a, f(a)) and (b, f(b)).
  • Rolle's theorem is a special case of the Mean Value Theorem where f(a) = f(b), making the right-hand side zero.

Angle of Intersection of Two Curves

  • The angle between two curves at a point of intersection is defined as the angle between their tangents at that common point.
  • If m₁ and m₂ are the slopes of the tangents to the two curves at the point, the acute angle θ between them satisfies tan θ = |(m₁ - m₂) / (1 + m₁m₂)|.
  • Orthogonal curves: the curves cut at right angles when m₁ × m₂ = -1 (so 1 + m₁m₂ = 0 and θ = 90°).
  • The curves touch each other (are tangential) when m₁ = m₂ at the point of intersection, giving θ = 0.
  • Method: find the point(s) of intersection, compute dy/dx for each curve there to get m₁ and m₂, then apply the formula.

Differentials, Errors and Approximation of Errors

  • The differential dy is defined by dy = f'(x) dx, where dx = Δx is the change in x. It measures the change along the tangent line, while the actual change Δy = f(x + Δx) - f(x) is along the curve.
  • For small Δx, dy ≈ Δy, which is what makes differentials useful for approximating values and estimating errors.
  • Absolute error in y is approximately |dy| = |f'(x)| |Δx|.
  • Relative error = Δy/y and percentage error = (Δy/y) × 100.
  • Example: if the radius of a sphere is measured as 9 cm with a possible error of 0.03 cm, then V = (4/3)πr³ gives dV = 4πr² dr = 4π(81)(0.03) = 9.72π cm³, the approximate error in the computed volume.

🚀 JEE Advanced Edge

Using AM-GM instead of calculus for optimization: Many "maximize/minimize" problems that look like they need derivatives can be solved faster with the AM-GM inequality (AM≥GM, equality when all terms are equal) — e.g. minimizing x+1/x for x>0 gives minimum value 2 instantly (since AM of x and 1/x ≥ GM = 1, so x+1/x≥2), without setting up and solving f'(x)=0. Recognizing when a problem is an AM-GM problem in disguise saves significant time.

Why the second derivative test can fail and when to fall back to the first: If f''(c)=0 at a critical point, the second derivative test gives NO information — the point could be a max, min, or inflection point (e.g. f(x)=x⁴ at x=0 has f''(0)=0 but is actually a minimum; f(x)=x³ at x=0 has f''(0)=0 and is an inflection point). Whenever f''(c)=0, you MUST revert to the first derivative test (sign change analysis) to classify the point correctly.

Worked problem: A wire of length 28m is cut into two pieces, one bent into a circle and the other into a square, to minimize the combined area. If x is the length used for the circle, find the value of x that minimizes total area. Approach: Circle circumference=x, so radius=x/(2π), area₁=πr²=x²/(4π). Square side=(28-x)/4, area₂=(28-x)²/16. Total A=x²/(4π)+(28-x)²/16. dA/dx = x/(2π) - (28-x)/8 = 0. Solving: 8x = 2π(28-x) → 8x+2πx=56π → x(8+2π)=56π → x=56π/(8+2π)=28π/(4+π).

Worked Example: Maxima and Minima

Find the local maximum and minimum values of f(x) = 2x³ − 9x² + 12x + 1.

f′(x) = 6x² − 18x + 12 = 6(x² − 3x + 2) = 6(x−1)(x−2). Critical points: x = 1 and x = 2.

f″(x) = 12x − 18. At x = 1: f″(1) = −6 < 0 → local max, f(1) = 6. At x = 2: f″(2) = 6 > 0 → local min, f(2) = 5. The second-derivative test decides max/min at each critical point.

Worked Example: Equation of Tangent

Find the equation of the tangent to y = x³ at the point (1, 1).

dy/dx = 3x². At x = 1, slope m = 3. Tangent: y − 1 = 3(x − 1) → y = 3x − 2. For NEET questions: find the derivative, substitute the given x-value for slope, then use point-slope form.

2Revise~4 min before the exam

📐 Formula Sheet

  • Rate of change: dy/dt = (dy/dx)(dx/dt)
  • Tangent slope at (x₁, y₁) = f'(x₁)  |  Normal slope = −1/f'(x₁)
  • Tangent line: y − y₁ = f'(x₁)(x − x₁)
  • Increasing: f'(x) > 0  |  Decreasing: f'(x) < 0
  • Critical points: f'(x) = 0 or f'(x) undefined
  • Second derivative test: f''(x) > 0 ⇒ local minimum; f''(x) < 0 ⇒ local maximum; f''(x) = 0 ⇒ test fails, use the first derivative
  • Absolute extrema on [a, b]: compare f at all critical points and at both endpoints
  • Approximation: f(x + Δx) ≈ f(x) + f'(x)·Δx
3Practiceapply it

✍️ Worked Examples

Example 1 — Related rates
Q: A balloon's radius grows at 2 cm/s. How fast is its volume growing when r = 5 cm?
Step 1 — Volume: V = (4/3)πr³.
Step 2 — Differentiate with respect to time: dV/dt = 4πr²·(dr/dt).
Step 3 — Substitute r = 5 and dr/dt = 2: dV/dt = 4π(25)(2) = 200π.
Answer: 200π ≈ 628 cm³/s. Key idea: the chain rule links the two rates; substitute numbers only after differentiating.

Example 2 — Maximum and minimum
Q: Find the local extrema of f(x) = x³ − 3x.
Step 1 — Differentiate: f'(x) = 3x² − 3 = 3(x² − 1) = 3(x − 1)(x + 1).
Step 2 — Critical points: f'(x) = 0 at x = 1 and x = −1.
Step 3 — Second derivative: f''(x) = 6x. At x = 1, f'' = 6 > 0 ⇒ minimum. At x = −1, f'' = −6 < 0 ⇒ maximum.
Step 4 — Values: f(1) = 1 − 3 = −2; f(−1) = −1 + 3 = 2.
Answer: local maximum 2 at x = −1, local minimum −2 at x = 1.

Example 3 — Optimisation
Q: A farmer has 100 m of fencing for a rectangular field. What dimensions maximise the area?
Step 1 — Constraint: 2x + 2y = 100 ⇒ y = 50 − x.
Step 2 — Express area in one variable: A = xy = x(50 − x) = 50x − x².
Step 3 — Differentiate and set to zero: A' = 50 − 2x = 0 ⇒ x = 25.
Step 4 — Confirm a maximum: A'' = −2 < 0 ✓. Then y = 50 − 25 = 25.
Answer: a 25 m × 25 m square, area 625 m². General rule: for a fixed perimeter, the square always maximises area.

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Frequently Asked Questions — Application of Derivatives

What are the key concepts in Application of Derivatives?
Use derivatives to study rate of change, increasing and decreasing functions, tangents and normals, and maxima and minima, with classic optimization problems.
Is Application of Derivatives important for JEE?
Yes. Application of Derivatives is part of the Mathematics Class 12 NCERT syllabus and is directly tested in JEE examinations. StudyHub provides structured notes, diagrams, and practice questions covering all exam-level subtopics.
How can I practice Application of Derivatives questions on StudyHub?
Open StudyHub and select Mathematics → Application of Derivatives. Choose Easy, Medium, or Hard difficulty. Hard-tier questions are at JEE level with full step-by-step explanations.

References

  1. NCERT Class 12 Mathematics Textbook — Chapter: Application of Derivatives
  2. CBSE Curriculum — Mathematics (Class 12)
  3. NTA JEE Main Official Syllabus — subject-wise topic list