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Transcript
Lesson 7
NYS COMMON CORE MATHEMATICS CURRICULUM
M3
ALGEBRA II
Lesson 7: Bacteria and Exponential Growth
Student Outcomes

Students solve simple exponential equations numerically.
Lesson Notes
The lessons in Topic A familiarized students with the laws and properties of real-valued exponents. Topic B introduces
the logarithm and develops logarithmic properties through exploration of logarithmic tables, primarily in base 10. This
lesson introduces simple exponential equations whose solutions do not follow from equating exponential terms of equal
bases. Because students have no sophisticated tools for solving exponential equations until logarithms are introduced in
later lessons, numerical methods must be used to approximate solutions to exponential equations, a process that asks
students to determine a recursive process from a context to solve 2π‘₯ = 10 (F-BF.A.1a, F-BF.B.4a, A-CED.A.1). Students
have many opportunities to solve such equations algebraically throughout the module, using both the technique of
equating exponents of exponential expressions with the same base and using properties of logarithms. The goals of this
lesson are to help students understand (1) why logarithms are useful by introducing a situation (i.e., solving 2π‘₯ = 10)
offering students no option other than numerical methods to solve it, (2) that it is often possible to solve equations
numerically by trapping the solution through better and better approximation, and (3) that the better and better
approximations are converging on a (possibly) irrational number.
Exponential equations are used frequently to model bacteria and population growth, and both of those scenarios occur
in this lesson.
Classwork
Opening Exercise (6 minutes)
In this exercise, students work in groups to solve simple exponential equations that can be solved by rewriting the
expressions on each side of the equation as a power of the same base and equating exponents. It is also possible for
students to use a table of values to solve these problems numerically; either method is valid, and both should be
discussed at the end of the exercise. Asking students to solve equations of this type demands that they think deeply
about the meaning of exponential expressions. Because students have not solved exponential equations previously, the
exercises are scaffolded to begin very simply and progress in difficulty; the early exercises may be merely solved by
inspection. When students are finished, ask for volunteers to share their solutions on the board and discuss different
solution methods.
Opening Exercise
Work with your partner or group to solve each of the following equations for 𝒙.
a.
𝒙
πŸ‘
𝟐 =𝟐
𝒙=πŸ‘
Lesson 7:
b.
𝒙
𝟐 =𝟐
𝒙=𝟏
Bacteria and Exponential Growth
This work is derived from Eureka Math β„’ and licensed by Great Minds. ©2015 Great Minds. eureka-math.org
This file derived from ALG II-M3-TE-1.3.0-08.2015
Scaffolding:

Encourage struggling students
to make a table of values of the
powers of 2 to use as a
reference for these exercises.
105
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Lesson 7
NYS COMMON CORE MATHEMATICS CURRICULUM
M3
ALGEBRA II
c.
πŸπ’™ = πŸπŸ”
d.
πŸπ’™ = πŸ”πŸ’
πŸπ’™ = πŸπŸ”
𝒙=πŸ”
πŸπ’™ = πŸπŸ’
𝒙=πŸ’
e.
πŸπ’™ βˆ’ 𝟏 = 𝟎
πŸπ’™ = 𝟏
πŸπ’™ = 𝟐𝟎
𝒙=𝟎
g.
πŸπ’™ βˆ’ πŸ”πŸ’ = 𝟎
f.
πŸπŸ‘π’™ = πŸ”πŸ’
πŸπŸ‘π’™ = πŸπŸ”
πŸ‘π’™ = πŸ”
𝒙=𝟐
πŸπ’™+𝟏 = πŸ‘πŸ
𝒙+𝟏
Scaffolding:
Give early finishers a more
challenging equation where
both bases need to be
changed, such as 42π‘₯ = 8π‘₯+3 .
πŸ“
𝟐
=𝟐
𝒙+𝟏= πŸ“
𝒙=πŸ’
Discussion (3 minutes)
This Discussion should emphasize that the equations in the Opening Exercise have straightforward solutions because
both sides can be written as an exponential expression with base 2.

MP.7
How did the structure of the expressions in these equations allow you to solve them easily?
οƒΊ

Suppose the Opening Exercise had asked us to solve the equation 2π‘₯ = 10 instead of the equation 2π‘₯ = 8.
Why is it far more difficult to solve the equation 2π‘₯ = 10?
οƒΊ

We do not know how to express 10 as a power of 2. In the Opening Exercise, it is straightforward that
8 can be expressed as 23 .
Can we find two integers that are under and over estimates of the solution to 2π‘₯ = 10? That is, can we find π‘Ž
and 𝑏 so that π‘Ž < π‘₯ < 𝑏?
οƒΊ

Both sides of the equations could be written as exponential expressions with base 2.
Yes; the unknown π‘₯ is between 3 and 4 because 23 < 10 < 24 .
In the next example, we will use a calculator (or other technology) to find a more accurate estimate of the
solutions to 2π‘₯ = 10.
Example (12 minutes)
The purpose of this exercise is to numerically pinpoint the solution 𝑑 to the equation 2𝑑 = 10 by squeezing the solution
between numbers that get closer and closer together. Start with 3 < 𝑑 < 4, and then find that 23.3 < 10 and 10 < 23.4 ,
so 3.3 < 𝑑 < 3.4. Continuing with this logic, squeeze 3.32 < 𝑑 < 3.33 and then 3.321 < 𝑑 < 3.322. The point of this
exercise is that it is possible to continue squeezing 𝑑 between numbers with more and more digits, meaning that there is
an approximation of 𝑑 to greater and greater accuracy.
In the student materials, the tables for the Discussion on the following pages are presented next to each other, but they
are spread out here to show how they fit into the Discussion.
Lesson 7:
Bacteria and Exponential Growth
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Lesson 7
NYS COMMON CORE MATHEMATICS CURRICULUM
M3
ALGEBRA II
Example
The Escherichia coli bacteria (commonly known as E. coli) reproduces once every πŸ‘πŸŽ minutes, meaning that a colony of
E. coli can double every half hour. Mycobacterium tuberculosis has a generation time in the range of 𝟏𝟐 to πŸπŸ” hours.
Researchers have found evidence that suggests certain bacteria populations living deep below the surface of the earth
may grow at extremely slow rates, reproducing once every several thousand years. With this variation in bacterial
growth rates, it is reasonable that we assume a πŸπŸ’-hour reproduction time for a hypothetical bacteria colony in this
example.
Suppose we have a bacteria colony that starts with 𝟏 bacterium, and the population of bacteria doubles every day.
What function 𝑷 can we use to model the bacteria population on day 𝒕?
𝑷(𝒕) = πŸπ’• , for real numbers 𝒕 β‰₯ 𝟎.
Have students volunteer values of 𝑃(𝑑) to help complete the following table.
𝒕
𝑷(𝒕)
𝟏
𝟐
𝟐
πŸ’
πŸ‘
πŸ–
πŸ’
πŸπŸ”
πŸ“
πŸ‘πŸ
How many days will it take for the bacteria population to reach πŸ–?
It will take πŸ‘ days because 𝑷(πŸ‘) = πŸπŸ‘ = πŸ–.
How many days will it take for the bacteria population to reach πŸπŸ”?
It will take πŸ’ days because 𝑷(πŸ’) = πŸπŸ’ = πŸπŸ”.
Roughly how long will it take for the population to reach 𝟏𝟎?
Between πŸ‘ and πŸ’ days; the number 𝒅 so that πŸπ’… = 𝟏𝟎
We already know from our previous discussion that if πŸπ’… = 𝟏𝟎, then πŸ‘ < 𝒅 < πŸ’, and the table confirms that. At this
point, we have an underestimate of πŸ‘ and an overestimate of πŸ’ for 𝒅. How can we find better under and over estimates
for 𝒅?
(Note to teacher: Once students respond, have them volunteer values to complete the table.)
Calculate the values of πŸπŸ‘.𝟏 , πŸπŸ‘.𝟐 , πŸπŸ‘.πŸ‘ , etc., until we find two consecutive values that have 𝟏𝟎 between them.
Lesson 7:
𝒕
𝑷(𝒕)
πŸ‘. 𝟏
πŸ–. πŸ“πŸ•πŸ’
πŸ‘. 𝟐
πŸ—. πŸπŸ—πŸŽ
πŸ‘. πŸ‘
πŸ—. πŸ–πŸ’πŸ—
πŸ‘. πŸ’
𝟏𝟎. πŸ“πŸ“πŸ”
Bacteria and Exponential Growth
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Lesson 7
NYS COMMON CORE MATHEMATICS CURRICULUM
M3
ALGEBRA II
From our table, we now know another set of under and over estimates for the number 𝒅 that we seek. What are they?
We know 𝒅 is between πŸ‘. πŸ‘ and πŸ‘. πŸ’. That is, πŸ‘. πŸ‘ < 𝒅 < πŸ‘. πŸ’.
Continue this process of β€œsqueezing” the number 𝒅 between two numbers until you are confident you know the value of
𝒅 to two decimal places.
MP.8
𝒕
𝑷(𝒕)
𝒕
𝑷(𝒕)
πŸ‘. πŸ‘πŸ
πŸ—. πŸ—πŸπŸ–
πŸ‘. πŸ‘πŸπŸ
πŸ—. πŸ—πŸ—πŸ’
πŸ‘. πŸ‘πŸ
πŸ—. πŸ—πŸ–πŸ•
πŸ‘. πŸ‘πŸπŸ
𝟏𝟎. 𝟎𝟎𝟏
πŸ‘. πŸ‘πŸ‘
𝟏𝟎. πŸŽπŸ“πŸ”
Since πŸ‘. πŸ‘πŸπŸ < 𝒅 < πŸ‘. πŸ‘πŸπŸ, and both numbers round to πŸ‘. πŸ‘πŸ, we can say that 𝒅 β‰ˆ πŸ‘. πŸ‘πŸ. We see that the population
reaches 𝟏𝟎 after πŸ‘. πŸ‘πŸ days (i.e., πŸπŸ‘.πŸ‘πŸ β‰ˆ 𝟏𝟎).
What if we had wanted to find 𝒅 to πŸ“ decimal places?
Keep squeezing 𝒅 between under and over estimates until they agree to the first πŸ“ decimal places. (Note to teacher: To πŸ“
decimal places, πŸ‘. πŸ‘πŸπŸπŸ—πŸπŸ– < 𝒅 < πŸ‘. πŸ‘πŸπŸπŸ—πŸπŸ—, so 𝒅 β‰ˆ πŸ‘. πŸ‘πŸπŸπŸ—πŸ‘.)
To the nearest minute, when does the population of bacteria become 𝟏𝟎?
It takes πŸ‘. πŸ‘πŸπŸ days, which is roughly πŸ‘ days, πŸ• hours, and πŸ’πŸ‘ minutes.
Discussion (2 minutes)

Could we repeat the same process to find the time required for the bacteria population to reach 20
(or 100 or 500)?
οƒΊ

Yes. We could start by determining between which two integers the solution to the equation
2𝑑 = 20 must lie and then continue the same process to find the solution.
Could we achieve the same level of accuracy as we did in the example? Could we make our solution more
accurate?
οƒΊ
Yes. We can continue to repeat the process and eventually β€œtrap” the solution to as many decimal
places as we would like.
Lead students to the idea that for any positive number π‘₯, they can repeat the process above to approximate the
exponent 𝐿 so that 2𝐿 = π‘₯ to as many decimal places of accuracy as they would like. Likewise, they can approximate an
exponent so that they can write the number π‘₯ as a power of 10 or a power of 3 or a power of 𝑒 or a power of any
positive number other than 1.
Note that there is a little bit of a theoretical hole here that is filled in later when the logarithm function is introduced. In
this lesson, students are only finding a rational approximation to the value of the exponent, which is the logarithm and is
generally an irrational number. That is, in this example, they are not truly writing 10 as a power of 2, but they are only
finding a close approximation. If students question this subtle point, let them know that later in the module they have
definitive ways to write any positive number exactly as a power of the base.
Lesson 7:
Bacteria and Exponential Growth
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Lesson 7
NYS COMMON CORE MATHEMATICS CURRICULUM
M3
ALGEBRA II
Exercise (8 minutes)
Divide students into groups of two or three, and assign each group a different equation to solve from the list below.
Students should repeat the process of the Example to solve these equations by squeezing the solution between more
and more precise under and over estimates. Record the solutions in a way that students can see the entire list either
written on poster board, written on the white board, or projected through the document camera.
Exercise
Use the method from the Example to approximate the solution to the equations below to two decimal places.
a.
πŸπ’™ = 𝟏𝟎𝟎𝟎
𝒙 β‰ˆ πŸ—. πŸ—πŸ•
b.
πŸ‘π’™ = 𝟏𝟎𝟎𝟎
𝒙 β‰ˆ πŸ”. πŸπŸ—
c.
πŸ’π’™ = 𝟏𝟎𝟎𝟎
𝒙 β‰ˆ πŸ’. πŸ—πŸ–
d.
πŸ“π’™ = 𝟏𝟎𝟎𝟎
𝒙 β‰ˆ πŸ’. πŸπŸ—
e.
πŸ”π’™ = 𝟏𝟎𝟎𝟎
𝒙 β‰ˆ πŸ‘. πŸ–πŸ”
f.
πŸ•π’™ = 𝟏𝟎𝟎𝟎
𝒙 β‰ˆ πŸ‘. πŸ“πŸ“
g.
πŸ–π’™ = 𝟏𝟎𝟎𝟎
𝒙 β‰ˆ πŸ‘. πŸ‘πŸ
h.
πŸ—π’™ = 𝟏𝟎𝟎𝟎
𝒙 β‰ˆ πŸ‘. πŸπŸ’
i.
πŸπŸπ’™ = 𝟏𝟎𝟎𝟎
𝒙 β‰ˆ 𝟐. πŸ–πŸ–
j.
πŸπŸπ’™ = 𝟏𝟎𝟎𝟎
𝒙 β‰ˆ 𝟐. πŸ•πŸ–
k.
πŸπŸ‘π’™ = 𝟏𝟎𝟎𝟎
𝒙 β‰ˆ 𝟐. πŸ”πŸ—
l.
πŸπŸ’π’™ = 𝟏𝟎𝟎𝟎
𝒙 β‰ˆ 𝟐. πŸ”πŸ
m.
πŸπŸ“π’™ = 𝟏𝟎𝟎𝟎
𝒙 β‰ˆ 𝟐. πŸ“πŸ“
n.
πŸπŸ”π’™ = 𝟏𝟎𝟎𝟎
𝒙 β‰ˆ 𝟐. πŸ’πŸ—
Discussion (2 minutes)

Do you observe a pattern in the solutions to the equations in the above Exercise?
οƒΊ
MP.3

Yes. The larger the base, the smaller the solution.
Why would that be?
οƒΊ
The larger the base, the smaller the exponent needs to be in order to reach 1,000.
Lesson 7:
Bacteria and Exponential Growth
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Lesson 7
NYS COMMON CORE MATHEMATICS CURRICULUM
M3
ALGEBRA II
Closing (4 minutes)
Have students respond to the following questions individually in writing or orally with a partner.

Explain when a simple exponential equation, such as those we have seen today, can be solved exactly using
our current methods.
οƒΊ

If both sides of the equation can be written as exponential expressions with the same base, then the
equation can be solved exactly.
When a simple exponential equation cannot be solved by hand, what can we do?
οƒΊ
We can give crude under and over estimates for the solution using integers.
οƒΊ
We can use a calculator to find increasingly accurate under and over estimates to the solution until we
are satisfied.
Exit Ticket (8 minutes)
Lesson 7:
Bacteria and Exponential Growth
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Lesson 7
NYS COMMON CORE MATHEMATICS CURRICULUM
M3
ALGEBRA II
Name
Date
Lesson 7: Bacteria and Exponential Growth
Exit Ticket
Loggerhead turtles reproduce every 2 to 4 years, laying approximately 120 eggs in a clutch. Using this information, we
can derive an approximate equation to model the turtle population. As is often the case in biological studies, we will
count only the female turtles. If we start with a population of one female turtle in a protected area and assume that all
turtles survive, we can roughly approximate the population of female turtles by 𝑇(𝑑) = 5𝑑 . Use the methods of the
Example to find the number of years, π‘Œ, it will take for this model to predict that there will be 300 female turtles. Give
your answer to two decimal places.
Lesson 7:
Bacteria and Exponential Growth
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Lesson 7
NYS COMMON CORE MATHEMATICS CURRICULUM
M3
ALGEBRA II
Exit Ticket Sample Solutions
Loggerhead turtles reproduce every 𝟐 to πŸ’ years, laying approximately 𝟏𝟐𝟎 eggs in a clutch. Using this information, we
can derive an approximate equation to model the turtle population. As is often the case in biological studies, we will
count only the female turtles. If we start with a population of one female turtle in a protected area and assume that all
turtles survive, we can roughly approximate the population of female turtles by 𝑻(𝒕) = πŸ“π’• . Use the methods of the
Example to find the number of years, 𝒀, it will take for this model to predict that there will be πŸ‘πŸŽπŸŽ female turtles. Give
your answer to two decimal places.
Since πŸ“πŸ‘ = πŸπŸπŸ“ and πŸ“πŸ’ = πŸ”πŸπŸ“, we know that πŸ‘ < 𝒀 < πŸ’.
Since πŸ“πŸ‘.πŸ“ β‰ˆ πŸπŸ•πŸ—. πŸ“πŸŽπŸ–πŸ’ and πŸ“πŸ‘.πŸ” β‰ˆ πŸ‘πŸπŸ–. πŸ‘πŸπŸ”πŸŽ, we know that πŸ‘. πŸ“ < 𝒀 < πŸ‘. πŸ”.
Since πŸ“πŸ‘.πŸ“πŸ’ β‰ˆ πŸπŸ—πŸ–. πŸŽπŸ—πŸ’πŸ’ and πŸ“πŸ‘.πŸ“πŸ“ β‰ˆ πŸ‘πŸŽπŸ. πŸ—πŸ‘πŸŽπŸ–, we know that πŸ‘. πŸ“πŸ’ < 𝒀 < πŸ‘. πŸ“πŸ“.
Since πŸ“πŸ‘.πŸ“πŸ’πŸ‘ β‰ˆ πŸπŸ—πŸ—. πŸ“πŸ‘πŸ•πŸ and πŸ“πŸ‘.πŸ“πŸ’πŸ’ β‰ˆ πŸ‘πŸŽπŸŽ. πŸŽπŸπŸ—πŸ”, we know that πŸ‘. πŸ“πŸ’πŸ‘ < 𝒀 < πŸ‘. πŸ“πŸ’πŸ’.
𝟏
𝟐
Thus, to two decimal places, we have 𝒀 β‰ˆ πŸ‘. πŸ“πŸ’. So, it will take roughly πŸ‘ years for the population to grow to πŸ‘πŸŽπŸŽ
female turtles.
Problem Set Sample Solutions
The Problem Set gives students an opportunity to practice using the numerical methods established in the lesson for
approximating solutions to exponential equations.
1.
Solve each of the following equations for 𝒙 using the same technique as was used in the Opening Exercise.
a.
πŸπ’™ = πŸ‘πŸ
b.
𝒙=πŸ“
d.
πŸπ’™ βˆ’ πŸπŸ’π’™βˆ’πŸ‘ = 𝟎
e.
2.
πŸ‘
𝟐
πŸπŸπ’™
πŸπ’™+πŸ“
f.
𝟐
πŸ‘
= πŸβˆ’πŸ
πŸπ’™
𝟐 βˆ’πŸπŸ”
=𝟏
𝟐
i.
𝟏
𝟐
πŸ‘π’™
𝟐
πŸ‘πŸ“π’™
= πŸ‘πŸ”
𝒙 = πŸ” or 𝒙 = βˆ’πŸ
= 𝟏 algebraically using two different initial steps as directed below.
Write each side as a power of 𝟐.
b.
Multiply both sides by πŸπ’™+πŸ“ .
πŸπŸπ’™ = πŸπ’™+πŸ“
πŸπŸπ’™βˆ’(𝒙+πŸ“) = 𝟐𝟎
πŸπ’™ = 𝒙 + πŸ“
π’™βˆ’πŸ“ =𝟎
𝒙=πŸ“
𝒙=πŸ“
Lesson 7:
𝟐 βˆ’πŸ‘π’™
𝒙 = πŸ’ or 𝒙 = βˆ’πŸ’
πŸ‘π’™ = πŸ–πŸ
𝒙=
Solve the equation
a.
h.
πŸπ’™
𝒙 = 𝟏 or 𝒙 = 𝟐
πŸπŸ‘π’™ βˆ™ πŸπŸ“ = πŸπŸ•
𝒙=
πŸ‘πŸπ’™ = πŸπŸ•
𝒙=
c.
𝒙 = βˆ’πŸ–
𝒙=𝟏
g.
πŸπ’™βˆ’πŸ‘ = πŸπŸπ’™+πŸ“
Bacteria and Exponential Growth
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Lesson 7
NYS COMMON CORE MATHEMATICS CURRICULUM
M3
ALGEBRA II
3.
Find consecutive integers that are under and over estimates of the solutions to the following exponential equations.
a.
πŸπ’™ = 𝟐𝟎
πŸπŸ’ = πŸπŸ” and πŸπŸ“ = πŸπŸ“, so πŸ’ < 𝒙 < πŸ“.
b.
πŸπ’™ = 𝟏𝟎𝟎
πŸπŸ” = πŸ”πŸ’ and πŸπŸ• = πŸπŸπŸ–, so πŸ” < 𝒙 < πŸ•.
c.
πŸ‘π’™ = πŸ“πŸŽ
πŸ‘πŸ‘ = πŸπŸ• and πŸ‘πŸ’ = πŸ–πŸ, so πŸ‘ < 𝒙 < πŸ’.
d.
πŸπŸŽπ’™ = πŸ’πŸ‘πŸ, πŸ—πŸŽπŸ
πŸπŸŽπŸ“ = 𝟏𝟎𝟎, 𝟎𝟎𝟎 and πŸπŸŽπŸ” = 𝟏, 𝟎𝟎𝟎, 𝟎𝟎𝟎, so πŸ“ < 𝒙 < πŸ”.
e.
πŸπ’™βˆ’πŸ = πŸ•πŸ“πŸŽ
πŸπŸ— = πŸ“πŸπŸ and 𝟐𝟏𝟎 = 𝟏, πŸŽπŸπŸ’, so πŸ— < 𝒙 βˆ’ 𝟐 < 𝟏𝟎; thus, 𝟏𝟏 < 𝒙 < 𝟏𝟐.
f.
πŸπ’™ = 𝟏. πŸ‘πŸ“
𝟐𝟎 = 𝟏 and 𝟐𝟏 = 𝟐, so 𝟎 < 𝒙 < 𝟏.
4.
Complete the following table to approximate the solution to πŸπŸŽπ’™ = πŸ‘πŸ’, πŸπŸ—πŸ– to three decimal places.
𝒙
πŸπŸŽπ’™
𝒙
πŸπŸŽπ’™
𝒙
πŸπŸŽπ’™
𝒙
πŸπŸŽπ’™
𝟏
𝟏𝟎
πŸ’. 𝟏
𝟏𝟐, πŸ“πŸ–πŸ—. πŸπŸ“πŸ’
πŸ’. πŸ“πŸ
πŸ‘πŸ, πŸ‘πŸ“πŸ—. πŸ‘πŸ”πŸ”
πŸ’. πŸ“πŸ‘πŸ
πŸ‘πŸ‘, πŸ—πŸ”πŸ. πŸ“πŸπŸ•
𝟐
𝟏𝟎𝟎
πŸ’. 𝟐
πŸπŸ“, πŸ–πŸ’πŸ–. πŸ—πŸ‘πŸ
πŸ’. πŸ“πŸ
πŸ‘πŸ‘, πŸπŸπŸ‘. 𝟏𝟏𝟐
πŸ’. πŸ“πŸ‘πŸ
πŸ‘πŸ’, πŸŽπŸ’πŸŽ. πŸ–πŸπŸ—
πŸ‘
𝟏, 𝟎𝟎𝟎
πŸ’. πŸ‘
πŸπŸ—, πŸ—πŸ“πŸ. πŸ”πŸπŸ‘
πŸ’. πŸ“πŸ‘
πŸ‘πŸ‘, πŸ–πŸ–πŸ’. πŸ’πŸπŸ”
πŸ’. πŸ“πŸ‘πŸ‘
πŸ‘πŸ’, πŸπŸπŸ—. πŸπŸ—πŸ
πŸ’
𝟏𝟎, 𝟎𝟎𝟎
πŸ’. πŸ’
πŸπŸ“, πŸπŸπŸ–. πŸ–πŸ”πŸ’
πŸ’. πŸ“πŸ’
πŸ‘πŸ’, πŸ”πŸ•πŸ‘. πŸ”πŸ–πŸ“
πŸ’. πŸ“πŸ‘πŸ’
πŸ‘πŸ’, πŸπŸ—πŸ•. πŸ—πŸ’πŸ’
πŸ“
𝟏𝟎𝟎, 𝟎𝟎𝟎
πŸ’. πŸ“
πŸ‘πŸ, πŸ”πŸπŸ. πŸ•πŸ•πŸ•
πŸ’. πŸ“πŸ‘πŸ“
πŸ‘πŸ’, πŸπŸ•πŸ”. πŸ•πŸ•πŸ—
πŸ’. πŸ”
πŸ‘πŸ—, πŸ–πŸπŸŽ. πŸ•πŸπŸ•
πŸπŸŽπ’™ = πŸ‘πŸ’, πŸπŸ—πŸ–
πŸπŸŽπŸ’.πŸ“πŸ‘πŸ’ β‰ˆ πŸ‘πŸ’, πŸπŸ—πŸ–, so 𝒙 β‰ˆ πŸ’. πŸ“πŸ‘πŸ’.
Lesson 7:
Bacteria and Exponential Growth
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Lesson 7
NYS COMMON CORE MATHEMATICS CURRICULUM
M3
ALGEBRA II
5.
Complete the following table to approximate the solution to πŸπ’™ = πŸπŸ— to three decimal places.
𝒙
πŸπ’™
𝒙
πŸπ’™
𝒙
πŸπ’™
𝒙
πŸπ’™
𝟏
𝟐
πŸ’. 𝟏
πŸπŸ•. πŸπŸ’πŸ–πŸ’
πŸ’. 𝟐𝟏
πŸπŸ–. πŸ“πŸŽπŸ•πŸŽ
πŸ’. πŸπŸ’πŸ
πŸπŸ–. πŸ—πŸŽπŸ—πŸŽ
𝟐
πŸ’
πŸ’. 𝟐
πŸπŸ–. πŸ‘πŸ•πŸ—πŸ
πŸ’. 𝟐𝟐
πŸπŸ–. πŸ”πŸ‘πŸ“πŸ•
πŸ’. πŸπŸ’πŸ
πŸπŸ–. πŸ—πŸπŸπŸ
πŸ‘
πŸ–
πŸ’. πŸ‘
πŸπŸ—. πŸ”πŸ—πŸ–πŸ‘
πŸ’. πŸπŸ‘
πŸπŸ–. πŸ•πŸ”πŸ“πŸ’
πŸ’. πŸπŸ’πŸ‘
πŸπŸ–. πŸ—πŸ‘πŸ“πŸ
πŸ’
πŸπŸ”
πŸ’. πŸπŸ’
πŸπŸ–. πŸ–πŸ—πŸ“πŸ—
πŸ’. πŸπŸ’πŸ’
πŸπŸ–. πŸ—πŸ’πŸ–πŸ‘
πŸ“
πŸ‘πŸ
πŸ’. πŸπŸ“
πŸπŸ—. πŸŽπŸπŸ•πŸ‘
πŸ’. πŸπŸ’πŸ“
πŸπŸ–. πŸ—πŸ”πŸπŸ“
πŸ’. πŸπŸ’πŸ”
πŸπŸ–. πŸ—πŸ•πŸ’πŸ”
πŸ’. πŸπŸ’πŸ•
πŸπŸ–. πŸ—πŸ–πŸ•πŸ–
πŸ’. πŸπŸ’πŸ–
πŸπŸ—. 𝟎𝟎𝟏𝟎
πŸπ’™ = πŸπŸ—
πŸπŸ’.πŸπŸ’πŸ– β‰ˆ πŸπŸ— , so 𝒙 β‰ˆ πŸ’. πŸπŸ’πŸ–.
6.
Approximate the solution to πŸ“π’™ = πŸ“πŸ“πŸ“πŸ“ to four decimal places.
Since πŸ“πŸ“ = πŸ‘πŸπŸπŸ“ and πŸ“πŸ” = πŸπŸ“β€†πŸ”πŸπŸ“, we know that πŸ“ < 𝒙 < πŸ”.
Since πŸ“πŸ“.πŸ‘ β‰ˆ πŸ“πŸŽπŸ”πŸ’. πŸ“πŸ“πŸπŸ— and πŸ“πŸ“.πŸ’ β‰ˆ πŸ“πŸ—πŸ’πŸ–. πŸ—πŸπŸ–πŸ”, we know that πŸ“. πŸ‘ < 𝒙 < πŸ“. πŸ’.
Since πŸ“πŸ“.πŸ‘πŸ“ β‰ˆ πŸ“πŸ’πŸ–πŸ–. πŸ—πŸ“πŸ‘πŸ and πŸ“πŸ“.πŸ‘πŸ” β‰ˆ πŸ“πŸ“πŸ•πŸ–. πŸŽπŸŽπŸ—πŸ, we know that πŸ“. πŸ‘πŸ“ < 𝒙 < πŸ“. πŸ‘πŸ”.
Since πŸ“πŸ“.πŸ‘πŸ“πŸ• β‰ˆ πŸ“πŸ“πŸ“πŸ. πŸπŸ’πŸπŸ• and πŸ“πŸ“.πŸ‘πŸ“πŸ– β‰ˆ πŸ“πŸ“πŸ”πŸŽ. πŸŽπŸ–πŸ‘πŸ, we know that πŸ“. πŸ‘πŸ“πŸ• < 𝒙 < πŸ“. πŸ‘πŸ“πŸ–.
Since πŸ“πŸ“.πŸ‘πŸ“πŸ•πŸ’ β‰ˆ πŸ“πŸ“πŸ“πŸ’. πŸ•πŸπŸ”πŸ“ and πŸ“πŸ“.πŸ‘πŸ“πŸ•πŸ“ β‰ˆ πŸ“πŸ“πŸ“πŸ“. πŸ”πŸπŸŽπŸ”, we know that πŸ“. πŸ‘πŸ“πŸ•πŸ’ < 𝒙 < πŸ“. πŸ‘πŸ“πŸ•πŸ“.
Since πŸ“πŸ“.πŸ‘πŸ“πŸ•πŸ’πŸ‘ β‰ˆ πŸ“πŸ“πŸ“πŸ’. πŸ—πŸ–πŸ’πŸ• and πŸ“πŸ“.πŸ‘πŸ“πŸ•πŸ’πŸ’ β‰ˆ πŸ“πŸ“πŸ“πŸ“. πŸŽπŸ•πŸ’πŸ, we know that πŸ“. πŸ‘πŸ“πŸ•πŸ’πŸ‘ < 𝒙 < πŸ“. πŸ‘πŸ“πŸ•πŸ’πŸ’.
Thus, the approximate solution to this equation to four decimal places is πŸ“. πŸ‘πŸ“πŸ•πŸ’.
7.
A dangerous bacterial compound forms in a closed environment but is immediately detected. An initial detection
reading suggests the concentration of bacteria in the closed environment is one percent of the fatal exposure level.
This bacteria is known to double in concentration in a closed environment every hour and can be modeled by the
function 𝑷(𝒕) = 𝟏𝟎𝟎 β‹… πŸπ’• , where 𝒕 is measured in hours.
a.
In the function 𝑷(𝒕) = 𝟏𝟎𝟎 β‹… πŸπ’• , what does the 𝟏𝟎𝟎 mean? What does the 𝟐 mean?
The 𝟏𝟎𝟎 represents the initial population of bacteria, which is 𝟏% of the fatal level. This means that the fatal
level occurs when 𝑷(𝒕) = 𝟏𝟎, 𝟎𝟎𝟎. The base 𝟐 represents the growth rate of the bacteria; it doubles every
hour.
b.
Doctors and toxicology professionals estimate that exposure to two-thirds of the bacteria’s fatal
concentration level will begin to cause sickness. Without consulting a calculator or other technology, offer a
rough time limit for the inhabitants of the infected environment to evacuate in order to avoid sickness.
𝟐
πŸ‘
The bacteria level is dangerous when 𝑷(𝒕) = 𝟏𝟎𝟎 β‹… πŸπ’• = (πŸπŸŽβ€†πŸŽπŸŽπŸŽ) β‰ˆ πŸ”πŸ”πŸ”πŸ”. πŸ”πŸ•.
Since πŸπŸ” = πŸ”πŸ’, 𝑷(πŸ”) β‰ˆ πŸ”πŸ’πŸŽπŸŽ, inhabitants of the infected area should evacuate within πŸ” hours.
Lesson 7:
Bacteria and Exponential Growth
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Lesson 7
NYS COMMON CORE MATHEMATICS CURRICULUM
M3
ALGEBRA II
c.
A more conservative approach is to evacuate the infected environment before bacteria concentration levels
reach one-third of fatal levels. Without consulting a calculator or other technology, offer a rough time limit
for evacuation in this circumstance.
𝟏
πŸ‘
Under these guidelines, the bacteria level is dangerous when 𝑷(𝒕) = 𝟏𝟎𝟎 β‹… πŸπ’• = (πŸπŸŽβ€†πŸŽπŸŽπŸŽ) β‰ˆ πŸ‘πŸ‘πŸ‘πŸ‘. πŸ‘πŸ‘.
Since πŸπŸ“ = πŸ‘πŸ, 𝑷(πŸ“) β‰ˆ πŸ‘πŸπŸŽπŸŽ, so the conservative approach is to recommend evacuation within πŸ“ hours.
Use the method of the Example to approximate when the bacteria concentration will reach 𝟏𝟎𝟎% of the fatal
exposure level, to the nearest minute.
d.
We need to approximate the solution to 𝟏𝟎𝟎 β‹… πŸπ’• = 𝟏𝟎, 𝟎𝟎𝟎, which is equivalent to solving πŸπ’• = 𝟏𝟎𝟎.
𝒕
πŸπ’•
𝒕
πŸπ’•
𝒕
πŸπ’•
𝒕
πŸπ’•
𝒕
πŸπ’•
𝟏
𝟐
πŸ”. 𝟏
πŸ”πŸ–. πŸ“πŸ—πŸ‘πŸ“
πŸ”. πŸ”πŸ
πŸ—πŸ•. πŸ”πŸ–πŸŽπŸ”
πŸ”. πŸ”πŸ’πŸ
πŸ—πŸ—. πŸ–πŸŽπŸπŸ
πŸ”. πŸ”πŸ’πŸ‘πŸ”
πŸ—πŸ—. πŸ—πŸ–πŸπŸ
𝟐
πŸ’
πŸ”. 𝟐
πŸ•πŸ‘. πŸ“πŸπŸ”πŸ•
πŸ”. πŸ”πŸ
πŸ—πŸ–. πŸ‘πŸ”πŸŽπŸŽ
πŸ”. πŸ”πŸ’πŸ
πŸ—πŸ—. πŸ–πŸ•πŸπŸ’
πŸ”. πŸ”πŸ’πŸ‘πŸ•
πŸ—πŸ—. πŸ—πŸ–πŸ—πŸ
πŸ‘
πŸ–
πŸ”. πŸ‘
πŸ•πŸ–. πŸ•πŸ—πŸ‘πŸ
πŸ”. πŸ”πŸ‘
πŸ—πŸ—. πŸŽπŸ’πŸ’πŸ
πŸ”. πŸ”πŸ’πŸ‘
πŸ—πŸ—. πŸ—πŸ’πŸŽπŸ•
πŸ”. πŸ”πŸ’πŸ‘πŸ–
πŸ—πŸ—. πŸ—πŸ—πŸ”πŸ
πŸ’
πŸπŸ”
πŸ”. πŸ’
πŸ–πŸ’. πŸ’πŸ’πŸ–πŸ“
πŸ”. πŸ”πŸ’
πŸ—πŸ—. πŸ•πŸ‘πŸ‘πŸ
πŸ”. πŸ”πŸ’πŸ’
𝟏𝟎𝟎. 𝟎𝟎𝟏𝟎
πŸ”. πŸ”πŸ’πŸ‘πŸ—
𝟏𝟎𝟎. πŸŽπŸŽπŸ‘πŸŽ
πŸ“
πŸ‘πŸ
πŸ”. πŸ“
πŸ—πŸŽ. πŸ“πŸŽπŸ—πŸ•
πŸ”. πŸ”πŸ“
𝟏𝟎𝟎. πŸ’πŸπŸ”πŸ–
πŸ”
πŸ”πŸ’
πŸ”. πŸ”
πŸ—πŸ•. πŸŽπŸŽπŸ“πŸ—
πŸ•
πŸπŸπŸ–
πŸ”. πŸ•
πŸπŸŽπŸ‘. πŸ—πŸ”πŸ–πŸ‘
Inhabitants need to evacuate within πŸ”. πŸ”πŸ’πŸ’ hours, which is approximately πŸ” hours and πŸ‘πŸ— minutes.
Lesson 7:
Bacteria and Exponential Growth
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This file derived from ALG II-M3-TE-1.3.0-08.2015
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