By the end of this chapter you'll be able to…

  • 1Decide which of the three readings a question needs: the value of the derivative, its sign, or a change in its sign
  • 2Estimate values and propagate measurement errors with the linear approximation, including the rule that a percentage error is multiplied by the power
  • 3Solve related-rates problems by writing the relation symbolically, differentiating with respect to time, and substituting only at the end
  • 4Determine intervals of increase and decrease, distinguishing isolated zeros of the derivative from an interval of them
  • 5Locate and classify critical points with the first and second derivative tests, and identify inflections by a genuine change in the sign of the second derivative
  • 6Find absolute extrema on a closed interval by comparing critical values with endpoint values, and set up optimisation problems in one variable
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Why this chapter matters in JEE Main
Five functions all have a stationary point at the origin, and they do five different things there. x squared has a minimum, minus x squared a maximum, x cubed neither, x to the fourth a minimum, and the modulus of x has a perfectly good minimum at a point where no derivative exists at all. Two of them share both a zero first derivative and a zero second derivative and still end up with opposite verdicts. So a vanishing derivative is neither necessary nor sufficient for an extremum, and the second derivative test is not the arbiter it looks like. Only one thing separates the five, and it is the same thing every time: does the derivative change sign there? That single question organises the whole unit, because the derivative's value tells you how fast, its sign tells you which way, and a change in its sign tells you where the function turns.

Before you start — revise these

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Differentiation rules including the chain, product and quotient rules, from Limits, Continuity and Differentiability
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Sign analysis of a factorised expression on a number line
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Standard mensuration formulas for the cone, cylinder, sphere and box
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Similar triangles, for setting up related-rates geometry

Application of Derivatives

Five functions. At , each has , except the last, where the derivative does not exist.

What is happening at the origin in each case?

At the origin
minimum
maximum
neither, and strictly increasing through it
minimum
undefinedundefinedminimum

Read the last three rows again. Two functions share and end up with opposite verdicts. A fifth has a perfectly good minimum at a point where no derivative exists at all.

x squaredminus x squared x cubedx to the fourth|x| minimummaximum neitherminimum minimum f'' = 0 heref'' = 0 here too no derivative at all only a SIGN CHANGE in f' decides, and it decides all five

Only one thing separates them, and it is the same thing in every case: does change sign there?

That is the whole unit in one idea.

What you needRead from the derivative
How fast something changesthe value of at a point
Which way it is goingthe sign of across an interval
Where it turnsa change of sign in

Ask which of the three the question wants, and the method follows with no decision to make.

1. The Derivative as a Rate of Change

is the rate at which changes per unit change in , at a particular point rather than averaged over an interval.

Positive means the quantities move together; negative means one rises as the other falls.

Approximate change and error

Over a small interval the graph is nearly straight.

That turns a derivative into an error estimate, which is how measurement error propagates through a calculation.

If a cube's side is cm with a possible error of cm, then gives cm.

As percentages, the side is uncertain by per cent and the volume by per cent, three times as much.

A percentage error is multiplied by the power. Cubing triples it, square-rooting halves it.

Illustration 1

Estimate without a calculator.

Choose the nearest point where the function is exactly known, which is , and treat the extra as a small step.

The true value is , so the estimate is high by , an error of about per cent.

The error is one-sided and predictable: is concave down, so its tangent line lies above the curve and every such estimate overshoots. Reading the concavity tells you the direction of the error before you check.

Most rate questions give one rate and ask for another. The link is always the chain rule, through the variable both depend on, usually time.

The method is fixed, and almost all lost marks here are procedural.

  1. Write the geometric relation, using no numerical values yet.
  2. Differentiate both sides with respect to , treating every variable as a function of time.
  3. Substitute the instantaneous values last.

Trap. Substituting a changing value before differentiating turns a variable into a constant, so its derivative becomes zero and the relation collapses. Genuinely fixed quantities, such as the length of a rigid ladder, may be substituted at any stage.

h r = h / 2 radius 5, height 10 2 cubic m per min in dh/dt depth h at h = 4, about 0.16 m per min a wide surface swallows the same inflow over a larger area constant inflow, changing rate of rise

Illustration 2

An inverted cone of height m and top radius m is filled at cubic metres per minute. How fast is the level rising when the depth is m?

Write the relation with both variables kept symbolic, and eliminate one using similar triangles.

Now differentiate with respect to time, and only then substitute.

Note what substituting too early would have done: is a constant, its derivative is zero, and the equation becomes .

At the same inflow raises the level only m per minute, four times slower, because the surface area has quadrupled.

Illustration 3

A person m tall walks away from a m lamp post at m per second. How fast does the tip of their shadow move?

Let be the distance from the post and the shadow's length. Similar triangles relate them.

The tip of the shadow sits at , so differentiate that.

The answer contains no at all: the tip moves at a constant speed wherever the person is. The shadow itself lengthens at m per second, and the difference between the two rates is exactly the walking speed.

Trap. "How fast is the shadow lengthening" and "how fast is the tip moving" are different questions with different answers. Decide which length the question is differentiating before writing anything.

3. Increasing and Decreasing Functions

Trap. Monotonicity is a property of an interval, not of a point. Saying a function is increasing at is meaningless in this syllabus.

A derivative may vanish at isolated points without breaking strict monotonicity. What matters is that it does not stay zero over an interval.

Illustration 4

Show that is strictly increasing on the whole real line.

Since always, everywhere, so the function never decreases.

It equals zero only where , that is at , which are isolated points, not an interval.

The graph confirms it: at each multiple of the curve flattens momentarily and then carries on upwards, exactly as does at the origin. A function stops being strictly increasing only if is zero across a whole interval, which would make it flat there.

Illustration 5

Find the intervals of increase and decrease of , and deduce which is larger, or .

The domain is . Differentiate by the quotient rule.

The denominator is positive throughout the domain, so the sign is entirely the numerator's.

So increases on and decreases on , with a maximum at of value .

Now use it. Since and decreases beyond :

The numbers are and , so the margin is genuinely small, and no amount of estimating would have settled it. Monotonicity did.

4. Critical Points and the Two Tests

Critical point. A point of the domain where or fails to exist.

The second half of that definition is what catches , and it is routinely forgotten.

The first derivative test

Examine the sign of on either side of the critical point.

Sign change in Verdict
to local maximum
to local minimum
no changeneither
local maximum local minimum ++ - f' rising falling rising the sign line is the whole test plus to minus is a peak, minus to plus a trough

The second derivative test

It is faster when it works, but is inconclusive and the first derivative test must then be used.

Concavity and inflection

means concave up; means concave down. An inflection is where the concavity changes, so is necessary but not sufficient: the second derivative must actually change sign.

inflection f'' less than 0: concave down f'' greater than 0: concave up the tangent crosses the curve here y = x^4 f'' = 0 here but no sign change f'' equal to zero is necessary for an inflection and never sufficient

Illustration 6

Find the inflection points of , and say why alone has none.

Now test whether the sign actually changes, which is the part that matters. The factor is positive outside and negative inside.

Both crossings are genuine sign changes, so there are inflections at , where .

For the second derivative is , which is zero at the origin but positive on both sides. No sign change, so no inflection: the curve is concave up throughout and merely flattens momentarily.

Illustration 7

Examine for local extrema.

Try the second derivative test first, since it is quicker.

Fall back on the sign of near . The factor is positive on both sides, so the sign is decided entirely by , which is negative on both sides of .

So is neither a maximum nor a minimum. It is a horizontal point of inflection: the curve flattens and carries on falling, exactly as does at the origin.

The minimum value is .

5. Absolute Maxima and Minima

On a closed interval, a continuous function attains both an absolute maximum and an absolute minimum, and each occurs either at a critical point or at an endpoint.

Trap. Endpoints are not critical points and the derivative need not vanish there, but they are legitimate places for the absolute extremum. Omitting them is the commonest error in this section.

Illustration 8

Find the absolute maximum and minimum of on .

Evaluate at that critical point and at both ends.

The minimum sits at an endpoint, where the derivative is rather than . Anyone who checked only the critical point would have reported as the maximum and had nothing at all to offer for the minimum.

6. Optimisation Problems

The procedure never varies.

  1. Name the quantity to be optimised and write it as a formula.
  2. Use the constraint to reduce it to one variable, noting the valid range.
  3. Differentiate, set to zero, and solve.
  4. Confirm it is the right kind of extremum, and check the endpoints of the range.

Illustration 9

Find the cylinder of greatest volume that can be inscribed in a sphere of radius .

Let the cylinder have radius and height . The constraint is that its corners touch the sphere, which by Pythagoras in the axial cross-section gives a relation between them.

Substitute to leave one variable, choosing because appears only as .

Compare with the sphere's own volume : the ratio is , so the best cylinder fills about per cent of the sphere.

Illustration 10

A closed cylindrical can must hold a fixed volume . What shape uses the least metal?

Surface area is what to minimise, and the volume is the constraint that removes one variable.

Rather than computing numerically, substitute back and see what shape emerges.

The answer is a proportion rather than a number, so it holds for every volume. That is what makes it worth remembering, and why real cans, which are taller than this, are shaped by printing and handling rather than by metal cost.

7. A Note on Syllabus Emphasis

The current unit text lists exactly three applications: rate of change of quantities, monotonic increasing and decreasing functions, and maxima and minima of functions of one variable.

Named in the JEE Main unitNot named
rate of changetangents and normals
monotonicityRolle's theorem
maxima and minimaLagrange's mean value theorem

All three unnamed topics remain examinable in JEE Advanced. The equation of a tangent is still worth the two minutes it takes to learn, since it is a direct reading of the derivative as a slope, but it should not displace practice on optimisation, where the marks in this unit actually sit.

Illustration 11

Beyond JEE Main, for Advanced sitters: prove that for all real and .

Lagrange's mean value theorem says that for a function differentiable on an interval, some interior point has slope equal to the average slope across it.

Take moduli, and use the fact that a cosine never exceeds in size.

The inequality says the sine graph is never steeper than a line of gradient , which is visible in its shape. Turning a visual fact into a proof is what the mean value theorem is for.

Summary

One number, three readings: the value says how fast, the sign says which way, a change of sign says where it turns.

is neither necessary nor sufficient for an extremum. Only a sign change in decides, which is why and behave differently at the origin and why has a minimum with no derivative at all.

estimates values and propagates errors, and a percentage error is multiplied by the power: cubing triples it.

For related rates, write the relation symbolically, differentiate with respect to time, then substitute. Substituting early makes a variable constant and collapses the equation.

Eliminate variables using the geometry before differentiating, as with in a cone.

Monotonicity is a property of an interval, not of a point. Isolated zeros of do not break strict monotonicity, but a whole interval of them does.

A sign analysis of solves inequality-flavoured questions such as which of and is larger.

Critical points include those where fails to exist, not only where it vanishes.

The second derivative test is faster when it works, and is inconclusive whenever ; the first derivative test always works.

is necessary but not sufficient for an inflection, since must actually change sign.

On a closed interval, compare the values at every critical point and at both endpoints; the absolute extremum is frequently at an endpoint.

For optimisation, reduce to one variable using the constraint, note the valid range, then differentiate. Answers that come out as proportions, such as height equalling diameter, hold for every size.

Key formulas & results

Everything to memorise for the exam hall, in one card. Screenshot this for revision.

The organising principle
value says how fast, sign says which way, change of sign says where it turns
All three applications in the unit are those three readings of one number. Ask which the question wants and the method follows with no decision to make.
Linear approximation
Estimates a nearby value and propagates measurement error. For the square root at 25 it gives root 26 as 5.1 against a true 5.09902, and the concavity predicts that the estimate overshoots.
Percentage error and powers
for V = a^n, the relative error in V is n times the relative error in a
Cubing triples a percentage error and square-rooting halves it. A cube side known to 0.2 per cent gives a volume known to 0.6 per cent.
Related rates procedure
write the relation symbolically, differentiate with respect to t, substitute values last
Substituting a changing value before differentiating makes it a constant, so its derivative is zero and the equation collapses. Genuinely fixed lengths may be substituted at any stage.
Eliminating a variable by geometry
use the similar-triangle or Pythagorean relation to reduce to one variable before differentiating
In a cone with radius 5 and height 10, r = h/2 turns the volume into pi h cubed over 12, after which one differentiation answers the question.
Monotonicity
f' greater than 0 on an interval means strictly increasing; f' less than 0 means strictly decreasing
Monotonicity is a property of an interval, not of a point. Isolated zeros of f' do not break strict monotonicity, which is why x minus sin x increases everywhere.
Critical points
points of the domain where f'(x) = 0 OR f'(x) fails to exist
The second half is routinely forgotten, and it is exactly what catches the modulus of x, whose minimum sits at a point with no derivative.
First derivative test
f' from + to - is a maximum, from - to + is a minimum, no change is neither
Always works. For x to the fourth minus 4x cubed, f' is negative on both sides of the origin, so that stationary point is a horizontal inflection rather than an extremum.
Second derivative test
f'(c) = 0 with f''(c) less than 0 gives a maximum, with f''(c) greater than 0 a minimum
Faster when it works, but f''(c) = 0 is inconclusive and the first derivative test must then be used. Both x cubed and x to the fourth land in that inconclusive case with opposite answers.
Concavity and inflection
f'' greater than 0 is concave up, less than 0 concave down; an inflection needs f'' to CHANGE SIGN
f'' equal to zero is necessary but never sufficient. For x to the fourth, f'' equals 12x squared, which touches zero at the origin without changing sign, so there is no inflection.
Absolute extrema on a closed interval
evaluate f at every critical point and at both endpoints, then compare
Endpoints are not critical points and the derivative need not vanish there, but they are legitimate winners. For sin x plus cos x on 0 to pi the minimum is minus 1 at the endpoint.
Optimisation procedure
name the quantity, use the constraint to reduce to one variable, note the valid range, differentiate
The cylinder of greatest volume in a sphere of radius R has height 2R over root 3 and fills about 58 per cent of the sphere.
Answers as proportions
a minimal-surface closed cylinder has height equal to diameter, whatever its volume
When the constraint cancels, the answer is a shape rather than a number and holds for every size. Such results are worth remembering because they cost nothing to reuse.
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Traps JEE Main sets — and how to dodge them

These are the exact option-traps and misreads that cost marks under negative marking.

WATCH OUT
Treating a zero derivative as proof of a maximum or minimum
Only a sign change in f' settles it. x cubed has f' equal to 3x squared, which is non-negative on both sides of the origin, so there is no extremum there and the function is strictly increasing through the point. Test the sign on both sides before committing.
Why it happens: Every worked example met early has a stationary point that really is an extremum.
WATCH OUT
Reporting inconclusive when the second derivative test fails
f''(c) equal to zero says only that this particular test cannot decide. The first derivative test always works. For x to the fourth minus 4x cubed at the origin, the sign of f' is negative on both sides, so it is a horizontal inflection, and the same test at x = 3 confirms a minimum of minus 27.
Why it happens: The test is presented as the standard method, so its failure looks like the end of the road.
WATCH OUT
Substituting instantaneous values before differentiating in a related-rates problem
A changing value substituted early becomes a constant with derivative zero, and the relation collapses to nonsense such as 2 equals 0. Keep every changing quantity symbolic, differentiate with respect to time, then substitute. Only genuinely fixed lengths may go in early.
Why it happens: The numbers are given in the question and it feels efficient to put them in early.
WATCH OUT
Ignoring endpoints when finding absolute extrema on a closed interval
The absolute extremum occurs at a critical point or at an endpoint, and endpoints frequently win. For sin x plus cos x on the interval from 0 to pi, the maximum is root 2 at an interior point but the minimum is minus 1 at the endpoint.
Why it happens: The routine is remembered as differentiate and solve, and endpoints have no vanishing derivative to find.
WATCH OUT
Declaring an inflection wherever the second derivative vanishes
An inflection requires the concavity to change, so f'' must change sign rather than merely touch zero. For x to the fourth, f'' equals 12x squared, which is positive on both sides of the origin, so there is no inflection there at all.
Why it happens: The condition f'' equal to zero is the only one usually stated.
WATCH OUT
Saying a function is increasing at a point
Increasing and decreasing are properties of intervals in this syllabus. State the interval, and remember that isolated zeros of f' inside it are harmless: x minus sin x has f' equal to zero at every multiple of two pi and is still strictly increasing on the whole real line.
Why it happens: The derivative is evaluated at a point, so the property seems to belong to the point.

Exam-pattern practice

PYQ-style questions with full solutions. Work through them as a readiness check — mark yourself honestly and get your gap report at the end.

Readiness check

Are you exam-ready for Application of Derivatives?

12 problems from this chapter. Try each one, reveal the worked solution, mark yourself honestly — get your gap report at the end.

12 questions~8 min

5-minute revision

The whole chapter, distilled. Read this the night before the exam.

  • Value says how fast, sign says which way, change of sign says where it turns
  • A zero derivative is neither necessary nor sufficient for an extremum
  • Delta y is approximately f' times delta x; percentage error is multiplied by the power
  • Related rates: relation symbolic, differentiate in t, substitute last
  • Eliminate a variable by similar triangles or Pythagoras before differentiating
  • Monotonicity belongs to intervals; isolated zeros of f' are harmless
  • Critical points include where f' does not exist
  • The first derivative test always works; the second is faster but fails when f'' is zero
  • An inflection needs f'' to change sign, not merely to vanish
  • On a closed interval, always evaluate at both endpoints as well
  • Optimisation: reduce to one variable using the constraint, then note the valid range
  • Answers that come out as proportions, like height equals diameter, hold for every size

JEE Main question blueprint

How this topic is asked, tier by tier — so you can prep to the pattern.

Typical weightage: 8

Question styleMarks eachTypical countWhat it tests
Rates of change and related rates21
Increasing, decreasing and monotonicity21
Maxima, minima and optimisation41

Exam-hall strategy

Battle-tested tips from mentors and toppers for this topic under the sectional clock.

  1. Decide first which of the three readings the question wants. How fast means evaluate the derivative, which way means analyse its sign, where it turns means look for a sign change. That single decision picks the method.
  2. Factorise the derivative before doing anything else with it. A factorised f' makes the sign chart immediate and often removes the need for a second derivative entirely.
  3. In related-rates questions, write the relation with letters only and draw a labelled diagram before touching a number. Almost every lost mark in this section is procedural rather than conceptual.
  4. On a closed interval, write the endpoint values into your comparison table before you start finding critical points. That way they cannot be forgotten, and they win more often than students expect.
  5. After solving an optimisation problem, sanity-check the answer against the physical range. A negative length, a radius exceeding the sphere, or a stationary point outside the permitted interval all signal an algebraic slip rather than a surprising result.

Beyond the exam

Where this skill shows up in the job you're competing for — and in life.

Engineering tolerance analysis uses the linear approximat…

Engineering tolerance analysis uses the linear approximation directly: a component machined to 0.2 per cent on a linear dimension is accurate only to 0.6 per cent by volume, which is why mass specifications are harder to meet than length ones

Container and packaging design is the minimal-surface pro…

Container and packaging design is the minimal-surface problem, and the result that height should equal diameter explains why cans that deviate from it are shaped by printing area and shelf handling rather than by material cost

Fluid level control in tanks depends on the fact that a c…

Fluid level control in tanks depends on the fact that a constant inflow does not give a constant rise: a conical or spherical vessel fills quickly when shallow and slowly when deep, and a controller that assumes linearity overshoots

Where else this topic is tested

Prepare once, score in every exam that asks it.

JEE Main
JEE Advanced
CBSE Class 12 Boards
BITSAT
WBJEE

Questions aspirants ask

Pulled from the Q&A community and mentor sessions.

Because a stationary point only says the tangent is horizontal, and a curve can be horizontal for a moment while continuing in the same direction. That is exactly what x cubed does at the origin: its derivative is three x squared, which is zero there but positive on both sides, so the function rises, flattens for an instant, and keeps rising. There is no turning point at all. What actually defines a maximum or minimum is that the function stops going one way and starts going the other, which is a change of sign in the derivative. The vanishing derivative is a useful place to look, because a smooth turning point must have one, but it is only a shortlist and every candidate has to be tested.

It fails whenever f''(c) equals zero, and it fails silently, in the sense that the test simply returns no information rather than a wrong answer. The two standard cases are x cubed and x to the fourth at the origin, which have identical first and second derivatives there and completely different behaviour, so no refinement of the test could separate them. When you land in that case, use the first derivative test: check the sign of f' on either side of the critical point. That test never fails, and it is often quicker than computing a second derivative in the first place, particularly when f' is already factorised. A practical habit is to factorise f' before differentiating again, because the factorised form usually makes the sign obvious.

Because differentiation acts on how a quantity varies, and a number does not vary. If you substitute the radius as 4 before differentiating, the expression becomes a constant, its derivative is zero, and the equation you were trying to build reduces to something like 2 equals 0. The correct order is to write the geometric relation with every changing quantity kept symbolic, differentiate the whole relation with respect to time so that each variable contributes its own rate through the chain rule, and only then put in the instantaneous values the question supplies. Quantities that genuinely never change, such as the length of a rigid ladder or the fixed half-angle of a cone, may be substituted at any stage, because their derivatives really are zero.

Keep the one that makes the constraint easiest to apply, and prefer the one that appears in the objective only as a square or higher power, since the constraint can then eliminate it without a square root. For a cylinder inscribed in a sphere, the volume is pi r squared h and the constraint gives r squared directly in terms of h, so keeping h avoids surds entirely. It also helps to look at what the question asks for: if it wants a height, expressing everything in terms of height saves a step at the end. Whichever you choose, write down the valid range of that variable before differentiating, because the range supplies the endpoints you must check and often rules out a spurious root.

The current JEE Main unit text names only three applications: rate of change, monotonicity, and maxima and minima. Tangents and normals are not named, and neither are Rolle's theorem nor Lagrange's mean value theorem, though all appear in older books and question banks. They remain firmly examinable in JEE Advanced, so an Advanced candidate should keep them. For Main, the equation of a tangent is still worth the two minutes it takes, because it is a direct reading of the derivative as a slope and costs almost nothing to learn. What it should not do is displace practice on optimisation, which is where the marks in this unit actually sit and which takes far longer to become fluent in.
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