Precalculus V. J. Motto Exponential/Logarithmic Part 1.

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Precalculu s V. J. Motto Exponential/Logarithmic Part 1

Transcript of Precalculus V. J. Motto Exponential/Logarithmic Part 1.

Page 1: Precalculus V. J. Motto Exponential/Logarithmic Part 1.

PrecalculusV. J. Motto

Exponential/Logarithmic Part 1

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Exponential and Logarithmic Functions4

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Chapter Overview

In this chapter, we study a new class

of functions called exponential functions.

• For example, f(x) = 2x

is an exponential function (with base 2).

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Chapter Overview

Notice how quickly the values of this function

increase:

f(3) = 23 = 8

f(10) = 210 = 1,024

f(30) = 230 = 1,073,741,824

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Chapter Overview

Compare that with the function

g(x) = x2

where g(30) = 302 = 900.

• The point is, when the variable is in the exponent, even a small change in the variable can cause a dramatic change in the value of the function.

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Chapter Overview

In spite of this incomprehensibly huge growth,

exponential functions are appropriate for

modeling population growth for all living

things—from bacteria to elephants.

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Chapter Overview

To understand how a population grows,

consider the case of a single bacterium,

which divides every hour.

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Chapter Overview

After one hour, we would have 2 bacteria;

after two hours, 22 or 4 bacteria; after three

hours, 23 or 8 bacteria; and so on.

• After x hours, we would have 2x bacteria.

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Chapter Overview

This leads us to model the bacteria

population by the function

f(x) = 2x

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Chapter Overview

The principle governing population

growth is:

• The larger the population, the greater the number of offspring.

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Chapter Overview

This same principle is present in

many other real-life situations.

• For example, the larger your bank account, the more interest you get.

• So, we also use exponential functions to find compound interest.

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Chapter Overview

We use logarithmic functions—which are

inverses of exponential functions—to help

us answer such questions as:

When will my investment grow to $100,000?

• In Focus on Modeling, we explore how to fit exponential and logarithmic models to data.

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Exponential Functions4.1

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Introduction

We now study one of the most

important functions in mathematics—

the exponential function.

• This function is used to model such natural processes as population growth and radioactive decay.

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Exponential Functions

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Exponential Functions

In Section 1-2, we defined ax for a > 0 and x

a rational number.

However, we have not yet defined irrational

powers.

• So, what is meant by or 2π?35

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Exponential Functions

To define ax when x is irrational,

we approximate x by rational numbers.

• For example, since

is an irrational number, we successively approximate by these rational powers:

3 1.73205...

3a

1.7 1.73 1.732 1.7320 1.73205, , , , , ...a a a a a

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Exponential Functions

Intuitively, we can see that these rational

powers of a are getting closer and closer

to .

• It can be shown using advanced mathematics that there is exactly one number that these powers approach.

• We define to be this number.

3a

3a

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Exponential Functions

For example, using a calculator,

we find:

• The more decimal places of we use in our calculation, the better our approximation of .

• It can be proved that the Laws of Exponents are still true when the exponents are real numbers.

3 1.7325 5 16.2411...

335

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Exponential Function—Definition

The exponential function with base a

is defined for all real numbers x by:

f(x) = ax

where a > 0 and a ≠ 1.

• We assume a ≠ 1 because the function f(x) = 1x = 1 is just a constant function.

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Exponential Functions

Here are some examples:

f(x) = 2x

g(x) = 3x

h(x) = 10x

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E.g. 1—Evaluating Exponential Functions

Let f(x) = 3x and evaluate the following:

(a) f(2)

(b) f(–⅔)

(c) f(π)

(d) f( )

• We use a calculator to obtain the values of f.

2

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E.g. 1—Evaluating Exp. Functions

Calculator keystrokes: 3, ^, 2, ENTER

Output: 9

• Thus, f(2) = 32 = 9

Example (a)

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E.g. 1—Evaluating Exp. Functions

Calculator keystrokes:

3, ^, (, (–), 2, ÷, 3, ), ENTER

Output: 0.4807498

• Thus, f(–⅔) = 3–⅔ ≈ 0.4807

Example (b)

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E.g. 1—Evaluating Exp. Functions

Calculator keystrokes: 3, ^, π, ENTER

Output: 31.5442807

• Thus, f(π) = 3π ≈ 31.544

Example (c)

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E.g. 1—Evaluating Exp. Functions

Calculator keystrokes: 3, ^, √, 2, ENTER

Output: 4.7288043

• Thus, f( ) = ≈ 4.7288

Example (d)

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Graphs of

Exponential Functions

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We first graph exponential functions

by plotting points.

• We will see that these graphs have an easily recognizable shape.

Graphs of Exponential Functions

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Draw the graph of each function.

(a) f(x) = 3x

(b) g(x) = (⅓)x

E.g. 2—Graphing Exp. Functions by Plotting Points

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First, we calculate values of f(x)

and g(x).

E.g. 2—Graphing Exp. Functions by Plotting Points

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Then, we the plot points to sketch

the graphs.

E.g. 2—Graphing Exp. Functions by Plotting Points

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Notice that:

• So, we could have obtained the graph of g from the graph of f by reflecting in the y-axis.

1 1( ) 3 ( )

3 3

xx

xg x f x

E.g. 2—Graphing Exp. Functions by Plotting Points

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Graphs of Exponential Functions

The figure shows the graphs of the family

of exponential functions f(x) = ax for various

values of the base a.

• All these graphs pass through the point (0, 1) because a0 = 1 for a ≠ 0.

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Graphs of Exponential Functions

You can see from the figure that there are

two kinds of exponential functions:

• If 0 < a < 1, the function decreases rapidly.

• If a > 1, the function increases rapidly.

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Graphs of Exponential Functions

The x-axis is a horizontal asymptote for

the exponential function f(x) = ax.

This is because:

• When a > 1, we have ax → 0 as x → –∞.

• When 0 < a < 1, we have ax → 0 as x → ∞.

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Graphs of Exponential Functions

Also, ax > 0 for all .

So, the function f(x) = ax has domain

and range (0, ∞).

• These observations are summarized as follows.

x

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Graphs of Exponential Functions

The exponential function

f(x) = ax (a > 0, a ≠ 1)

has domain and range (0, ∞).

• The line y = 0 (the x-axis) is a horizontal asymptote of f.

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Graphs of Exponential Functions

The graph of f has one of these

shapes.

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E.g. 3—Identifying Graphs of Exponential Functions

Find the exponential function f(x) = ax

whose graph is given.

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E.g. 3—Identifying Graphs

Since f(2) = a2 = 25, we see that

the base is a = 5.

• Thus, f(x) = 5x

Example (a)

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E.g. 3—Identifying Graphs

Since f(3) = a3 = 1/8 , we see that

the base is a = ½ .

• Thus, f(x) = (½)x

Example (b)

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Graphs of Exponential Functions

In the next example, we see how to graph

certain functions—not by plotting points—

but by:

1. Taking the basic graphs of the exponential functions in Figure 2.

2. Applying the shifting and reflecting transformations of Section 2-4.

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E.g. 4—Transformations of Exponential Functions

Use the graph of f(x) = 2x to sketch the graph

of each function.

(a) g(x) = 1 + 2x

(b) h(x) = –2x

(c) k(x) = 2x –1

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E.g. 4—Transformations

To obtain the graph of g(x) = 1 + 2x,

we start with the graph of f(x) = 2x and

shift it upward 1 unit.

• Notice that the line y = 1 is now a horizontal asymptote.

Example (a)

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E.g. 4—Transformations

Again, we start with

the graph of f(x) = 2x.

However, here,

we reflect in the x-axis

to get the graph of

h(x) = –2x.

Example (b)

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E.g. 4—Transformations

This time, we start with

the graph of f(x) = 2x

and shift it to the right

by 1 unit—to get

the graph of k(x) = 2x–1.

Example (c)

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E.g. 5—Comparing Exponential and Power Functions

Compare the rates of growth of the

exponential function f(x) = 2x and the power

function g(x) = x2 by drawing the graphs of

both functions in these viewing rectangles.

(a) [0, 3] by [0, 8]

(b) [0, 6] by [ 0, 25]

(c) [0, 20] by [0, 1000]

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E.g. 5—Exp. and Power Functions

The figure shows that the graph of

g(x) = x2 catches up with, and becomes

higher than, the graph of f(x) = 2x at x = 2.

Example (a)

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E.g. 5—Exp. and Power Functions

The larger viewing rectangle here shows

that the graph of f(x) = 2x overtakes that

of g(x) = x2 when x = 4.

Example (b)

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E.g. 5—Exp. and Power Functions

This figure gives a more global view

and shows that, when x is large, f(x) = 2x

is much larger than g(x) = x2.

Example (c)

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The Natural

Exponential Function

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Natural Exponential Function

Any positive number can be used as the base

for an exponential function.

However, some are used more frequently

than others.

• We will see in the remaining sections of the chapter that the bases 2 and 10 are convenient for certain applications.

• However, the most important is the number denoted by the letter e.

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Number e

The number e is defined as the value

that (1 + 1/n)n approaches as n becomes

large.

• In calculus, this idea is made more precise through the concept of a limit.

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Number e

The table shows

the values of the

expression (1 + 1/n)n

for increasingly large

values of n.

• It appears that, correct to five decimal places,

e ≈ 2.71828

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Number e

The approximate value to 20 decimal

places is:

e ≈ 2.71828182845904523536

• It can be shown that e is an irrational number.

• So, we cannot write its exact value in decimal form.

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Number e

Why use such a strange base for

an exponential function?

• It may seem at first that a base such as 10 is easier to work with.

• However, we will see that, in certain applications, it is the best possible base.

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Natural Exponential Function—Definition

The natural exponential function is

the exponential function

f(x) = ex

with base e.

• It is often referred to as the exponential function.

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Natural Exponential Function

Since 2 < e < 3, the graph of the natural

exponential function lies between

the graphs of y = 2x

and y = 3x.

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Natural Exponential Function

Scientific calculators have a special

key for the function f(x) = ex.

• We use this key in the next example.

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E.g. 6—Evaluating the Exponential Function

Evaluate each expression correct to five

decimal places.

(a) e3

(b) 2e–0.53

(c) e4.8

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E.g. 6—Evaluating the Exponential Function

We use the ex key on a calculator to

evaluate the exponential function.

(a) e3 ≈ 20.08554

(b) 2e–0.53 ≈ 1.17721

(c) e4.8 ≈ 121.51042

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E.g. 7—Transformations of the Exponential Function

Sketch the graph of each function.

(a) f(x) = e–x

(b) g(x) = 3e0.5x

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E.g. 7—Transformations

We start with the graph of y = ex and reflect

in the y-axis

to obtain the graph

of y = e–x.

Example (a)

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E.g. 7—Transformations

We calculate several values, plot

the resulting points, and then connect

the points with a smooth curve.

Example (b)

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E.g. 8—An Exponential Model for the Spread of a Virus

An infectious disease begins to spread

in a small city of population 10,000.

• After t days, the number of persons who have succumbed to the virus is modeled by:

0.97

10,000( )

5 1245 tv t

e

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(a) How many infected people are there

initially (at time t = 0)?

(b) Find the number of infected people after

one day, two days, and five days.

(c) Graph the function v and describe

its behavior.

E.g. 8—An Exponential Model for the Spread of a Virus

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E.g. 8—Spread of Virus

• We conclude that 8 people initially have the disease.

Example (a)

0(0) 10,000 /(5 1245 )

10,000 /1250

8

v e

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E.g. 8—Spread of Virus

Using a calculator, we evaluate v(1), v(2),

and v(5).

Then, we round off to obtain these values.

Example (b)

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E.g. 8—Spread of Virus

From the graph, we see that the number

of infected people:

• First, rises slowly.

• Then, rises quickly between day 3 and day 8.

• Then, levels off when about 2000 people are infected.

Example (c)

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Logistic Curve

This graph is called a logistic curve or

a logistic growth model.

• Curves like it occur frequently in the study of population growth.

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Compound Interest

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Compound Interest

Exponential functions occur in

calculating compound interest.

• Suppose an amount of money P, called the principal, is invested at an interest rate i per time period.

• Then, after one time period, the interest is Pi, and the amount A of money is:

A = P + Pi + P(1 + i)

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Compound Interest

If the interest is reinvested, the new principal

is P(1 + i), and the amount after another time

period is:

A = P(1 + i)(1 + i) = P(1 + i)2

• Similarly, after a third time period, the amount is:

A = P(1 + i)3

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Compound Interest

In general, after k periods,

the amount is:

A = P(1 + i)k

• Notice that this is an exponential function with base 1 + i.

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Compound Interest

Now, suppose the annual interest rate is r and

interest is compounded n times per year.

Then, in each time period, the interest rate

is i = r/n, and there are nt time periods

in t years.

• This leads to the following formula for the amount after t years.

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Compound Interest

Compound interest is calculated by

the formula

where:• A(t) = amount after t years

• P = principal

• t = number of years

• n = number of times interest is compounded per year

• r = interest rate per year

( ) 1n t

rA t P

n

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E.g. 9—Calculating Compound Interest

A sum of $1000 is invested at an interest rate

of 12% per year.

Find the amounts in the account after 3 years

if interest is compounded:• Annually• Semiannually• Quarterly• Monthly• Daily

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E.g. 9—Calculating Compound Interest

We use the compound interest formula

with: P = $1000, r = 0.12, t = 3

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Compound Interest

We see from Example 9 that the interest

paid increases as the number of

compounding periods n increases.

• Let’s see what happens as n increases indefinitely.

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Compound Interest

If we let m = n/r, then

/

( ) 1

1

11

n t

r tn r

r tm

rA t P

n

rP

n

Pm

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Compound Interest

Recall that, as m becomes large,

the quantity (1 + 1/m)m approaches

the number e.

• Thus, the amount approaches A = Pert.

• This expression gives the amount when the interest is compounded at “every instant.”

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Continuously Compounded Interest

Continuously compounded interest is

calculated by

A(t) = Pert

where:• A(t) = amount after t years

• P = principal

• r = interest rate per year

• t = number of years

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E.g. 10—Continuously Compounded Interest

Find the amount after 3 years if $1000

is invested at an interest rate of 12%

per year, compounded continuously.

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E.g. 10—Continuously Compounded Interest

We use the formula for continuously

compounded interest with:

P = $1000, r = 0.12, t = 3

• Thus, A(3) = 1000e(0.12)3 = 1000e0.36

= $1433.33

• Compare this amount with the amounts in Example 9.