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Application of Derivatives.
Rates, slopes and the best possible.

A derivative measures how fast something changes. That one idea answers three kinds of question. How fast is a ripple's area growing? Where is a graph rising and where is it falling? What shape of box, can or window is the best possible?

Where the tangent points up (f′ > 0) the curve rises; where it points down (f′ < 0) it falls. At the top of a hill and the bottom of a valley the tangent is flat: f′ = 0.
Part 1 · Sections 6.1–6.2

A derivative is a rate of change.

A derivative tells you how fast one quantity changes when another one changes. That speed of change is called a rate.

The idea
dydx = f′(x)

If y = f(x), this is the rate of change of y with respect to x: how much y changes per unit change of x. f′(x₀) is that rate at x = x₀. (Derivatives are in Chapter 5.)

Rates in time
dAdt = dAdr · drdt

When several quantities change with time t, the chain rule links their rates: differentiate with respect to r, then multiply by how fast r changes.

Both depend on t
dydx = dy/dtdx/dt

If x = f(t) and y = g(t), divide the two time rates. This needs dx/dt ≠ 0.

Money rates
MC = dCdx,  MR = dRdx

In economics, marginal cost and marginal revenue are rates with respect to x, the number of items.

Ripple labA ripple's radius grows at dr/dt. Each second a thin ring of width dr/dt is added, and its length is the circumference 2πr. So dA/dt = 2πr · dr/dt: bigger ripples gain area faster.
dA/dt = 2πr · dr/dt
Watch out

A quantity that is decreasing has a negative rate. In Example 4 the length shrinks at 3 cm/min, so dx/dt = −3.

Example 1

Rate of change of the area of a circle w.r.t. r at r = 5.

  1. dA/dr = 2πr.
10π.
Example 2

Cube volume grows 9 cm³/s; surface rate at x = 10.

  1. dx/dt = 3/x², dS/dt = 36/x.
3.6 cm²/s.
Example 3

Ripple at 4 cm/s, r = 10.

  1. dA/dt = 2πr · dr/dt.
80π cm²/s.
Example 4

Rectangle: dx/dt = −3, dy/dt = 2 at x = 10, y = 6.

  1. dP/dt = 2(dx/dt + dy/dt); dA/dt = y dx/dt + x dy/dt.
−2 cm/min; 2 cm²/min.
Example 5

Marginal cost at x = 3.

  1. MC = 0.015x² − 0.04x + 30.
₹30.02.
Example 6

Marginal revenue at x = 5.

  1. MR = 6x + 36.
₹66.
Part 2 · Section 6.3

The sign of f′ tells you up or down.

Where the slope f′ is positive the graph climbs; where it is negative the graph falls. So the sign of f′ tells you up or down.

Increasing
x₁ < x₂  ⇒  f(x₁) ≤ f(x₂)

for any x₁, x₂ in an interval I: moving right never takes you down. If always f(x₁) < f(x₂), f is strictly increasing.

Decreasing
x₁ < x₂  ⇒  f(x₁) ≥ f(x₂)

The same with the inequality reversed (strictly decreasing: f(x₁) > f(x₂)). If f(x) = c throughout, f is constant.

Theorem 1
f′ ≥ 0  ⇒  increasing
f′ ≤ 0  ⇒  decreasing

(f′ on all of (a, b), as the book prints it.) And f′ = 0 makes f constant. This holds when f is continuous on [a, b] and differentiable on (a, b): the sign of f′ on (a, b) decides f on [a, b].

How to use it

  1. Find f′(x) and solve f′(x) = 0.
  2. These points split the number line into pieces.
  3. Test one point in each piece to read the sign of f′ there.
  4. Plus sign: f is increasing on that piece. Minus sign: decreasing.
Up-and-down labSlide the point along the curve. The tangent is green while f′ > 0 and red while f′ < 0; the strip under the graph shows the sign of f′ everywhere.
f′(x)
Example 7

7x − 3 on R.

  1. x₁ < x₂ ⇒ 7x₁ − 3 < 7x₂ − 3.
Strictly increasing.
Example 8

x³ − 3x² + 4x.

  1. f′ = 3(x − 1)² + 1 > 0.
Increasing on R.
Example 9

cos x on (0, 2π).

  1. f′ = −sin x.
Down on (0, π), up on (π, 2π).
Example 10

x² − 4x + 6.

  1. f′ = 2x − 4 = 0 at 2.
Down on (−∞, 2), up on (2, ∞).
Example 11

4x³ − 6x² − 72x + 30.

  1. f′ = 12(x + 2)(x − 3).
Up, down on (−2, 3), up.
Example 12

sin 3x on [0, π/2].

  1. f′ = 3 cos 3x = 0 at π/6.
Up on [0, π/6], down on [π/6, π/2].
Example 13

sin x + cos x on [0, 2π].

  1. f′ = 0 at π/4, 5π/4.
Up, down on (π/4, 5π/4), up.
Part 3 · Section 6.4

Hill tops and valley bottoms are where f′ = 0.

The tops of hills and bottoms of valleys sit where the tangent is flat, or where the slope does not exist, like at a sharp corner.

Max and min
f(c) ≥ f(x) for every x in I

Then f(c) is the maximum value of f on I. With ≤ instead of ≥, it is the minimum value.

Local
f(c) ≥ f(x) for x near c

c is a local maximum if this holds just in some small interval around c: the top of one hill, not of the whole graph. A local minimum is the same with ≤.

Theorem 2
f′(c) = 0
or no f′(c) at all

At a local maximum or minimum, either f′(c) = 0 or f is not differentiable at c. Such points are called critical points.

How to use it · first derivative test

  1. Find the critical points c.
  2. Look at the sign of f′ just to the left and just to the right of each c.
  3. From + to −: c is a local maximum. From − to +: a local minimum.
  4. No change of sign: neither. c is a point of inflection (as for x³ at 0).
Basics for thissignssolving f′ = 0
First derivative testPick a function. Each critical point is labelled by how f′ changes as you walk through it from left to right.
Example 14

x² on R.

  1. x² ≥ 0 = f(0).
Min 0; no max.
Example 15

|x| on R.

  1. Corner at 0.
Min 0; no max.
Example 16

x on (0, 1).

  1. Open ends: always a smaller and a bigger value.
Neither.
Example 17

x³ − 3x + 3.

  1. f′ = 3(x − 1)(x + 1).
Max 5 at −1, min 1 at 1.
Example 18

2x³ − 6x² + 6x + 5.

  1. f′ = 6(x − 1)² ≥ 0.
Inflection at 1.
Example 19

3 + |x|.

  1. Not differentiable at 0; first derivative test.
Local min 3.
Part 4 · Section 6.4 · Second derivative test

A cup has f″ > 0; a cap has f″ < 0.

The second derivative f″ tells you how the graph bends. At a flat point, a cup shape means a bottom and a cap shape means a top.

Cup: a bottom
f′(c) = 0,  f″(c) > 0

c is a local minimum. A positive f″ means the slope is increasing, so the graph curves up like a cup and the flat point must be a bottom.

Cap: a top
f′(c) = 0,  f″(c) < 0

c is a local maximum. A negative f″ means the slope is decreasing, so the graph curves down like a cap.

When it fails
f″(c) = 0

The test fails: it does not decide. Go back to the first derivative test.

How to use it · Theorem 4

  1. Solve f′(x) = 0 to find the flat points c.
  2. Work out f″(x) and put in each c.
  3. f″(c) < 0: local maximum. f″(c) > 0: local minimum. f″(c) = 0: use the first derivative test.
Basics for thisrates of rates
Cup or capMove the point. The readouts show f′ and f″; where f′ = 0, the sign of f″ decides.
f′(x)
f″(x)
Example 20

3x⁴ + 4x³ − 12x² + 12.

  1. f″(0) < 0, f″(1) > 0, f″(−2) > 0.
Max 12 at 0; min 7 at 1, −20 at −2.
Example 21

2x³ − 6x² + 6x + 5.

  1. f″(1) = 0: the test fails.
Inflection at 1.
Part 5 · Section 6.4.1

On a closed interval, compare the candidates.

On a closed interval the highest and lowest values always exist. List every candidate point, work out f at each, and compare.

Theorem 5
f continuous on [a, b]

Then f always has an absolute maximum and an absolute minimum on [a, b].

Theorem 6
f′(c) = 0

If one of them is attained at an interior point c (not an end point), then f′ = 0 there.

Open interval
f(x) = x on (0, 1)

On an open interval there may be neither: here there is always a bigger and a smaller value (Example 16).

How to use it · working rule

  1. Find the critical points of f in [a, b].
  2. Add the end points a and b.
  3. Evaluate f at all of them.
  4. The largest value is the absolute maximum; the smallest is the absolute minimum.
Interval labf(x) = 2x³ − 15x² + 36x + 1 (Example 27). Move the ends of the interval: the winner can be a hill top, a valley bottom or an end point.
Example 27

2x³ − 15x² + 36x + 1 on [1, 5].

  1. Candidates 1, 2, 3, 5: values 24, 29, 28, 56.
Max 56, min 24.
Example 28

12x4/3 − 6x1/3 on [−1, 1].

  1. Critical points 0 (f′ undefined) and 1/8.
Max 18 at −1, min −9/4 at 1/8.
Example 29

Helicopter on y = x² + 7, soldier at (3, 7).

  1. Minimise (x − 3)² + x⁴.
√5.
Part 6 · Applications

Optimisation: build the function, then find its best value.

To find the best box, fence or can, write the quantity as a function of one variable. Then find its largest or smallest value.

How to use it

  1. Name the quantity Q to make largest or smallest.
  2. Use the given condition to write Q as a function of one variable x.
  3. Note which values x is allowed to take.
  4. Solve Q′(x) = 0.
  5. Check that it really is the maximum or minimum: use the second derivative, the first derivative test or the end points.
Box labAn 18 cm square of tin (Exercise 6.3 Q17). Cut a square of side x from each corner and fold up the flaps. Find the cut that holds the most.
volume V = x(18 − 2x)²
Example 22

Sum 15, least sum of squares.

  1. S = 2x² − 30x + 225.
15/2 and 15/2.
Example 23

Shortest distance from (0, c) to y = x².

  1. D(k) = √(k + (k − c)²).
√(4c − 1)/2.
Example 24

Poles 16 m, 22 m, 20 m apart.

  1. S = 2x² − 40x + 1140.
x = 10 m.
Example 25

Trapezium with three sides 10.

  1. A = (x + 10)√(100 − x²).
75√3 cm².
Example 26

Cylinder in a cone, most curved surface.

  1. S = (2πh/r)(rx − x²).
x = r/2.
Miscellaneous examples

Put it all together.

Example 30

x = t²(2 − t/3): when does the car stop?

  1. v = 4t − t² = 0.
t = 4 s, PQ = 32/3 m.
Example 31

Inverted cone tank, 5 m³/h, depth 4 m.

  1. V = πh³/12.
35/88 m/h.
Example 32

Man 2 m, lamp 6 m, 5 km/h.

  1. l = 2s.
5/2 km/h.
Example 33

(3/10)x⁴ − (4/5)x³ − 3x² + (36/5)x + 11.

  1. f′ = (6/5)(x − 1)(x + 2)(x − 3).
Up on (−2, 1), (3, ∞).
Example 34

tan⁻¹(sin x + cos x) on (0, π/4).

  1. f′ = (cos x − sin x)/(2 + sin 2x) > 0.
Increasing.
Example 35

Disc r = 3.2, dr/dt = 0.05.

  1. dA/dt = 2πr dr/dt.
0.32π cm²/s.
Example 36

Box from a 3 × 8 sheet.

  1. V′ = 4(x − 3)(3x − 2).
200/27 m³.
Example 37

Price 5 − x/100, cost x/5 + 500.

  1. P′ = 24/5 − x/50.
240 items.
Self-check

The nine multiple-choice questions, and three more.

Twelve quick questions to check yourself. Tap an option to check it and see the reasoning.

Nine are every MCQ from Exercises 6.1–6.3 and the miscellaneous exercise; three are quick concept checks.

Score0 / 1212 left to answer
Summary

Remember this.

dy/dx is the rate of change of y with respect to x; with time as a link, dy/dx = (dy/dt)/(dx/dt) when dx/dt ≠ 0.

f′ ≥ 0 on (a, b) ⇒ increasing; f′ ≤ 0 ⇒ decreasing; f′ = 0 ⇒ constant (f continuous on [a, b]).

A critical point is where f′(c) = 0 or f is not differentiable. Local extrema can only happen there.

First derivative test: + to − gives a local max, − to + a local min, no change an inflection.

Second derivative test: f′(c) = 0 with f″(c) < 0 gives a max, f″(c) > 0 a min; f″(c) = 0 means the test fails.

Absolute extrema on [a, b]: evaluate f at the critical points and the end points; take the largest and the smallest.

A little history

Looking for the best.

c. 1636Fermat

Before calculus had a name, Fermat found maxima and minima by noticing that near a highest point a small change hardly changes the value: the idea behind f′ = 0.

1684Leibniz

His first calculus paper was titled, roughly, "a new method for maxima and minima, and for tangents".

1696L'Hôpital

The first calculus textbook explained how to find the highest and lowest points of curves.

1797Lagrange

He stated the Mean Value Theorem, the fact that turns "f′ > 0" into "f is increasing".

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