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Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2
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Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

Dec 25, 2015

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Page 1: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

Chapter 3Introduction to the

Derivative

Sections 3.5, 3.6, 4.1 and 4.2

Page 2: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

Introduction to the Derivative

Average Rate of Change

The Derivative

Page 3: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

change in

change in

f f

x x

( ) ( )f b f a

b a

The average rate of change of f (x) over the interval [a , b] is

The change of f (x) over the interval [a,b] is

( ) ( )f f b f a

Difference Quotient

Average Rate of Change

Page 4: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

Average Rate of Change

, ( )P a f a

, ( )Q b f b

secant line has slope mS

( ) ( )S PQ

f f b f am m

x b a

Is equal to the slope of the secant line through the points (a , f (a)) and (b , f (b)) on the graph of f (x)

x b a

( ) ( )f f b f a

Page 5: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

The average rate of change of f over the interval [a , b] can be written in two different ways:

( ) ( ) ( ) ( )f f b f a f a h f a

x b a h

Average Rate of Change as h0

Page 6: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

We now look at the behavior of the average rate of change of f (x) as b a h gets smaller and smaller, that is, we will let h tend to 0 (h0) and look for a geometric interpretation of the result.For this, we consider an example of values of

and their corresponding secant lines.

( ) ( )S PQ

f f a h f am m

x h

Average Rate of Change as h0

Page 7: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

2.57h

Average Rate of Change as h0Secant line tends to become the Tangent line

Page 8: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

2h

Average Rate of Change as h0Secant line tends to become the Tangent line

Page 9: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

1.5h

Average Rate of Change as h0Secant line tends to become the Tangent line

Page 10: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

1h

Average Rate of Change as h0Secant line tends to become the Tangent line

Page 11: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

0.5h

Average Rate of Change as h0Secant line tends to become the Tangent line

Page 12: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

0.2h

Average Rate of Change as h0Secant line tends to become the Tangent line

Page 13: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

Zoom in

0.1h

Average Rate of Change as h0Secant line tends to become the Tangent line

Page 14: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

0.1h

Average Rate of Change as h0Secant line tends to become the Tangent line

Page 15: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

0.05h

Average Rate of Change as h0Secant line tends to become the Tangent line

Page 16: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

( ) ( ) smallT S

f a h f am m h

h

We observe that as h approaches zero,

1. The secant line through P and Q approaches the tangent line to the point P on the graph of f.

2. and consequently, the slope mS of the secant line approaches the slope mT of the tangent line to the point P on the graph of f.

Average Rate of Change as h0

Page 17: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

That is, the limiting value, as h gets increasingly smaller, of the difference quotient

is the slope mT of the tangent line to the graph of the function f (x) at x = a.

( ) ( )S

f a h f am

h

Instantaneous Rate of Change of f at x = a

(slope of secant line)

Page 18: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

This is usually written as

( ) ( )as 0S T

f a h f am m h

h

Instantaneous Rate of Change of f at x = a

tends to, orapproaches

That is, mS approaches mT as h tends to 0.

Page 19: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

More briefly using symbols by writing

0

( ) ( )limTh

f a h f am

h

Instantaneous Rate of Change of f at x = a

and read0

limh

as “the limit as h approaches 0 of ”

Page 20: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

that is, the limit symbol indicates that the value of

can be made arbitrarily close to mT by taking h to be a sufficiently small number.

( ) ( )S

f a h f am

h

Instantaneous Rate of Change of f at x = a

Page 21: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

Definition: The instantaneous rate of change of f (x) at x = a is defined to be the slope of the tangent line to the graph of the function f (x) at x = a. That is,

0

( ) ( )lim "instantaneous rate of change at "Th

f a h f am a

h

Instantaneous Rate of Change of f at x = a

Remark: The slope mT gives a precise indication of how fast the graph of f (x) is increasing or decreasing at x = a.

Page 22: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

Consider the function f (x) – x2/4 + 9/4, whose graph is given below, at the points a – 3 and a – 1

A Concrete Example

At which of these two points is the function increasing faster?

Intuition says at x – 3 because we notice the graph is steeper at the point x – 3. Why?

Page 23: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

A Concrete Example

Because our brain makes no distinction between the graph of f and the tangent line to the graph at the point in question.

To make this more obvious we zoom in

Consider the function f (x) – x2/4 + 9/4, whose graph is given below, at the points a – 3 and a – 1

Page 24: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

A Concrete Example

We see how the tangent line basically coincides with the graph of f near the point of contact. What is the slope of each line? 1.5 at -3Tm x

0.5 at -1Tm x

Consider the function f (x) – x2/4 + 9/4, whose graph is given below, at the points a – 3 and a – 1

Page 25: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

A Concrete Example

That is, at the points of contact, the function is increasing as fast as its corresponding tangent line.

Consider the function f (x) – x2/4 + 9/4, whose graph is given below, at the points a – 3 and a – 1

Page 26: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

A Concrete Example

We now verify the claims by explicitly computing for this function, the limit,

0

( ) ( )limTh

f a h f am

h

Consider the function f (x) – x2/4 + 9/4, whose graph is given below, at the points a – 3 and a – 1

Page 27: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

For the function f (x) – x2/4 + 9/4 at any point a we have

A Concrete Example

2 9( )

4 4

af a

2 2 2( ) 9 9( )

4 4 4 2 4 4

a h a ah hf a h

2

( ) ( ) 2 42 4

ah hf a h f a a h

h h

Page 28: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

A Concrete Example

( ) ( )

2 4S

f a h f a a hm

h

Thus, for the function f (x) – x2/4 + 9/4 at any point a we have

Therefore, as h tends to 0, mS approaches – a/2 mT .

0 0

( ) ( )lim lim

2 4 2Th h

f a h f a a h am

h

Page 29: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

A Concrete ExampleFor the function f (x) – x2/4 + 9/4 at any point a we have

2T

am

Thus,

1.5 at -3Tm a

0.5 at -1Tm a

Page 30: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

A Concrete ExampleLet us try some other values of a for the same function.

0 at 0Tm a

0.5 at 1Tm a

1 at 2Tm a

1.5 at 3Tm a

2T

am

Page 31: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

Remark

2T

am

The example clearly indicates that the slope mT of the tangent line is itself a function of the point a we choose.

We need a better notation reflecting the fact that this object is a function of a

Page 32: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

The DerivativeThe instantaneous rate of change mT at a is also called the derivative of f at x = a and it is denoted by f '(a). That is,

0

( ) ( )( ) lim

h

f a h f af a

h

f '(a) is read “f prime of a”

mT = f '(a) = “slope of the tangent line to f (x) at a”

= “instantaneous rate of change of f at a”

Page 33: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

The DerivativeThe instantaneous rate of change mT at a is also called the derivative of f at x = a and it is denoted by f '(a). That is,

0

( ) ( )( ) lim

h

f a h f af a

h

In our previous example, the derivative of the function f (x) – (x2 – 9)/4 at any point a is given by

( )2

af a

Page 34: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

Rates of ChangeAverage rate of change of f over the interval [a, a+h] is

( ) ( )f f a h f a

x h

Instantaneous rate of change of f at x=a is

Slope of the secant line through the points (a , f (a)) and (a , f (a+h))

0

( ) ( )( ) lim

h

f a h f af a

h

Slope of the tangent line at the point (a , f (a))

Page 35: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

Tangent Line and Secant Line

, ( )a f a

, ( )a h f a h

secant line

tangent line at a

Page 36: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

Equation of Tangent Line at x = a

, ( )a f a

tangent line at a

( ) ( )( )y f a f a x a

Using the point-slope form of the line

Page 37: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

Finding the derivative of the function f is called differentiating f.

If f '(a) exists, then we say that f is differentiable at x = a.

For some functions f , f '(a) may not exist. In this case we say that the function f is not differentiable at x = a.

Terminology

Page 38: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

( ) ( )( )

f a h f af a

h

Recall that f '(a) is the limiting value of the expression

as we make h increasingly smaller. Therefore, we can approximate the numerical value of the derivative using small values of h. h = 0.001 often works. In this case,

Quick Approximation of the Derivative

( ) ( )f a h f a

h

Page 39: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

Demand: The demand for an old brand of TV is given by

where p is the price per TV set, in dollars, and q is the number of TV sets that can be sold at price p . Find q (190) and estimate q '(190) . Interpret your answers.

100,000

10q

p

Quick Approximation - Example

Page 40: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

Solution

100,000 100,000(190) 500

190 10 200q

(190 0.001) (190)

(190)0.001

q qq

499.9975 500(190) 2.5

0.001q

TV sets(190) 2.5

$q

Page 41: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

Geometric Interpretation

a 190

At a 190, q(p) decreases as fast as the tangent line does, that is, at the ratemT q '(190) 2.5 TVs/$

What does this means?

It means that at the price of p $190, the demand will decrease by 2.5 TV sets per dollar we increase the price.

If we now set the price at $200, how many TV sets do we expect to sell?

Page 42: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

Geometric Interpretation

p 200

At a 190, the equation of the tangent line is

y 2.5( p-190 )+500Thus, when we set the price at p $200, the line shows that we expect to sell y 475 TVs

The actual number we expect to sell according to the demand function is

q (200) 476.2 476 TVswhich is very close to the prediction given by the tangent line.

Page 43: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

Now Recall The Example The slope mT f '(a) of the tangent line depends on the point a we choose on the graph of f .

(0) 0Tm f

(1) 0.5Tm f

(3) 1.5Tm f

( )2T

am f a

(2) 1Tm f

Page 44: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

Chapter 4Techniques of

Differentiation with Applications

Sections 4.1 and 4.2

Page 45: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

Techniques of Differentiation

Derivatives of Powers, Sums and Constant asMultiples

Marginal Analysis

Page 46: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

The Derivative as a Function

0

( ) ( )( ) lim

h

f x h f xf x

h

If f is a function, its derivative function is the function whose value at x is the derivative of f at x. That is,

Notice that all we have done is substituted x for a in the definition of f '(a). This way, when we are done with the algebra, the answer will be given in terms of x.

Page 47: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

Example: Given the function

0 0

( )lim lim 1h h

x h x h

h h

( ) , find ( )f x x f x

0

( ) ( )( ) lim

h

f x h f xf x

h

Thus, if ( ) , then ( ) 1f x x f x

The Derivative as a Function

Page 48: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

Thus, if ( ) , then ( ) 1f x x f x

Geometric Verification At any point on the graph of f , the tangent line agrees with the graph of which already is a straight line of slope 1

Page 49: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

2 2 2

0

2limh

x xh h x

h

2( ) , find ( )f x x f x

2 2

0

( )limh

x h x

h

2

0

2limh

xh h

h

0lim(2 )h

x h

The Derivative as a Function

Example: Given the function

0

( ) ( )( ) lim

h

f x h f xf x

h

2Thus, if ( ) , then ( ) 2f x x f x x

Page 50: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

Geometric Verification

2Thus, if ( ) , then ( ) 2f x x f x x

x y=x2

-3

-2

-1

0

1

2

3

x y'=2x

-3

-2

-1

0

1

2

3

( )f x ( )f x

Page 51: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

3 2 2 3 3

0

3 3limh

x x h xh h x

h

3( ) , find ( )f x x f x

3 3

0

( )limh

x h x

h

2 2

0lim 3 3h

x xh h

2 2 3

0

3 3limh

x h xh h

h

Example: Given the function

0

( ) ( )( ) lim

h

f x h f xf x

h

3 2Thus, if ( ) , then ( ) 3f x x f x x

The Derivative as a Function

Page 52: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

The Power Rule

3.7( )g x x

11 ( )f x x

x

Example: 2.7( ) 3.7g x x

22

1 ( )f x x

x

1/ 33

1 ( )f x x

x 4 / 31

( )3

f x x

1

If ( ) , where is any constant, then

( )

n

n

f x x n

f x nx

Example:

Example:

Page 53: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

0limh

x h x x h x

h x h x

( ) , find ( )f x x f x

0limh

x h x

h

0

1limh x h x

0

limh

x h x

h x h x

Example: Given the function

0

( ) ( )( ) lim

h

f x h f xf x

h

1Thus, if ( ) , then ( )

2f x x f x

x

Verification when f (x) x1/2

Page 54: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

Leibniz’ d Notation For Derivatives

Average rate of change f

x

0limx

f df

x dx

Instantaneous rate of change

df

dx( ).f xmeans the same as

Page 55: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

Differential Notation: Differentiation

d

dxmeans “the derivative with respect to x”.

The derivative of y f (x) with respect to x is written

( )d dy

ydx dx

5 4If ( ) , then 5 .dy

y f x x xdx

or as ( )d df

f xdx dx

Example:

55 4( )

If ( ) , then 5 .d x

y f x x xdx

Page 56: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

Differential Notation: Differentiation

5If ( ) , then find ( 2)y f x x f Example:

5 4If ( ) , then find ( ) 5 and ( 2) 80y f x x f x x f

To find f '(2), the derivative of y f (x) at x 2, we first need to find the function f '(x).

In Leibniz’ notation f '(2) is denoted by the symbol

54 4

22 2

( )5 5( 2) 80

xx x

df d xx

dx dx

Page 57: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

Differentiation Rules

Example: If ( ) 14 then ( ) 0f x f x

1) 0 a constantd

c cdx

1

2) If ( ) , where is any constant, then

( )

n

n

f x x n

f x nx

Example: 2 / 3 1/ 32If ( ) then ( )

3f x x f x x

Page 58: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

3) ( ) ( ) a constantd d

cf x c f x cdx dx

8 8 7 7( ) 3 3 3 8 24f x x x x x

Differentiation Rules

Example: 8If ( ) 3 then f x x

8 8 7 7

or

3 3 3 8 24df d d

x x x xdx dx dx

Page 59: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

4) ( ) ( ) d d d

f x g x f x g xdx dx dx

2 12 11( ) 7 4 14 12f x x x x x

Differentiation Rules

Example: 2 12If ( ) 7 4 then f x x x

2 12 11

or

7 4 14 12df d d d

x x x xdx dx dx dx

Page 60: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

Example: Find the derivative of 2

3( )

2f x

x

2 23 3( )

2 2f x x x

First write f (x) as constant times a power 23( )

2f x x

2 2 33 3 3( ) 2

2 2 2f x x x x

2 2 3 33

3 3 3 3( ) 2 3

2 2 2f x x x x x

x

More Examples

Page 61: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

33

1 5( ) 4 7

4f x x

x x

1 1/ 3 31( ) 5 4 7

4f x x x x

First write f (x) as

1 1/ 3 31( ) 5 4 7

4f x x x x

2 4 / 3 21 1( ) 1 5 4 3 0

4 3f x x x x

1 1/ 3 31( ) 5 4 7

4f x x x x

2 4 / 3 21 5( ) 12

4 3f x x x x

Example: Find the derivative of

Page 62: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

Functions Not Differentiable at a Point

a) Vertical tangent x = a b) Cusp x = a

c) f (a) = Undefined

Page 63: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

Example: The Absolute Value of x.

( )f x x (0)f DNE

1 if 0( )

1 if 0

xf x

x

Page 64: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

Example: The cube root of x.1/ 33( )f x x x (0)f DNE

1/ 3 2 / 31( )

3f x x x

2 / 3

1( )

3f x

x

2 / 3

1(0)

3 0f DNE

Page 65: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

Introduction to the Derivative

Average Rate of Change

The Derivative

Derivatives of Powers, Sums and Constant asMultiples

Marginal Analysis

Page 66: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

Cost Functions

A cost function specifies the total cost C as a function of the number of items x produced. Thus, C(x) is the cost of x items. The cost functions is made up of two parts:

C(x)= “variable costs” + “fixed costs”

The marginal cost function is the derivative C′(x) of C(x). It measures the instantaneous rate of change of cost with respect to x.

Page 67: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

By definition the Marginal Cost Function is C′(x).

The units of marginal cost are units of cost (say, $) per item.

Interpretation: The marginal cost function C′(x) approximates the change in actual cost of producing an additional unit when x items are already being produced.

0

( ) ( )( ) lim

h

C x h C xC x

h

Page 68: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

Interpretation of Marginal Cost

The Marginal Cost Function is C′(x). Thus, for small h we have the quick approximation given by

( ) ( )( )

C x h C xC x

h

If we let h=1 (one more item being produced ), then

( 1) ( )( )

1

C x C xC x

Page 69: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

That is, for h=1, we have

( ) ( 1) ( )C x C x C x

Notice that C(x+1) - C(x) is the actual (exact) cost of producing one additional item when the production level is x.

In practice, h=1 is considered to be small in relation to production level x, which in general is a large number.

Interpretation of Marginal Cost

Page 70: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

Average Cost Functions

Given a cost function C(x) , the average cost function given by:

( )( )

C xC x

x

Total cost of producing items( )

xC x

x

Page 71: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

Example

The total monthly cost function C, in dollars, of producing x computer games is given by:

2( ) 0.001 20 3000 C x x x

a) Find the marginal cost function and use it to estimate the cost of producing the 1,001st game.

b) Find the actual cost of producing the 1,001st game.

Page 72: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

The marginal cost function is given by:

( ) 0.002 20C x x

An estimate for the cost of producing the 1,001st game is

(1000) 0.002(1000) 20 18C

That is, it costs an additional $18 to produce one more game when the production level is at 1,000 games a month

Solution

Page 73: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

The the actual cost of producing the 1,001st game

(1001) (1000) =C C

2

2

0.001(1001) 20(1001) 3000

0.001(1000) 20(1000) 3000

(1001) (1000) =22017.999-22000C C

(1001) (1000) = $17.999C C

Solution

Page 74: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

Example Continued

a) Find the average cost per game if 1,000 games are manufactured.

b) Find the average cost function.

The total monthly cost function C, in dollars, of producing x computer games is given by:

2( ) 0.001 20 3000 C x x x

Page 75: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

The average cost function:

20.001 20 3000x x

x

( )( )

C xC x

x

10.001 20 3000x x

(1000) 22,000(1000) 22 $ /

1000 1000

CC game

Solution

Page 76: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

More Marginal Functions

The Marginal Profit Function measures the rate of change of the profit function. It approximates the profit from the sale of an additional unit.

The Marginal Revenue Function measures the rate of change of the revenue function. It approximates the revenue from the sale of an additional unit.

Page 77: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

Given a revenue function, R(q), The Marginal Revenue Function is:

( )dR

R qdq

Given a profit function, P(q), The Marginal Profit Function is:

( )dP

P qdq

More Marginal Functions

Page 78: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

The monthly demand for T-shirts is given by

0.05 25 0 400p q q

where p denotes the wholesale unit price in dollars and q denotes the quantity demanded. The monthly cost for these T-shirts is $8 per shirt.

a) Find the revenue and profit functions.

b) Find the marginal revenue and marginal profit functions.

Marginal Functions - Examples

Page 79: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

2( ) 0.05 25 0.05 25 R q q q q q

2( ) 0.05 25 8P q q q q

a) Find the revenue and profit functions.

Revenue = qp

Profit = revenue – cost

2( ) 0.05 17P q q q

Solution

Page 80: Chapter 3 Introduction to the Derivative Sections 3.5, 3.6, 4.1 and 4.2.

b) Find the marginal revenue and marginal profit functions.

Marginal revenue 2( ) 0.05 25R q q q

0.1 25q

0.1 17q

2( ) 0.05 17P q q q Marginal profit

Solution