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Lesson 8-4 Modeling with Quadratic Functions

Lesson 8-4 Modeling with Quadratic Functions

Assessment

Presentation

Mathematics

9th - 10th Grade

Practice Problem

Medium

Created by

Laura Wroten

Used 3+ times

FREE Resource

21 Slides • 8 Questions

1

Lesson 8-4 Modeling with Quadratic Functions

By Laura Wroten

2

Bellringer

What is the value of f(12)?

This simply means to plug in 12 everywhere you see x in the equation.

Put it in your calculator now...​

Answer: A. 116

3

Vocabulary

The equation h(t) = -16t2+v0t+h0 is the vertical motion model. The variable h represents the height of an object, in feet, t seconds after it is launched into the air. The term v0 is the object's initial vertical velocity and h0 is its initial height.

Quadratic regression is a method used to find the quadratic function that best fits a data set. ​

4

Example 1 (Make sure you are looking at your notes)

Remember: A=LW

A. The length of the pool is 2x BUT there is also a 4ft wide deck on BOTH sides: L = 2x+8

The width of the pool is x BUT there is also a 4ft wide deck on BOTH sides: W = x+8

A=(2x+8)(x+8) -- Use the distributive property or box method to multiply.​

5

Multiple Choice

What is the simplified quadratic function?

f(x) = ___________________

1

2x2+24x+64

2

2x2+24x+16

3

2x2+64

4

2x2+16x+16

6

B. The paragraph tells us that the width of the pool is 15 feet, so we will plug 15 in for x.

f(15) = 2(15)2+24(15)+64

Put this in your calculator now to find the answer!​

7

Fill in the Blank

What is the answer to part B? (numbers only)

______ ft2

8

Multiple Select

Try It! 1. What will the new quadratic function be? Select all that apply.

1

(3x+8)(x+8)

2

(3x+4)(x+4)

3

3x(x+8)

4

3x2+32x+64

9

Example 2: h(t) = -16t2+v0t+h0

A. What do we know from the problem?

v0=16 (initial velocity)

h0=30 (initial height - from picture)

Plug those numbers into the equation to create your new equation.​

10

Multiple Choice

What is the new equation?

1

h(t) = -16t2+30t+16

2

h(t) = -16t2+16+30

3

h(t) = -16t2+16t+30

4

h(t) = -16t2+30+16

11

12

Multiple Choice

What is the x-value of the vertex?

1

12-\frac{1}{2}  

2

12\frac{1}{2}  

3

16

4

-2

13

Once we know that the x-value of our vertex is 1/2, we can plug that in to the equation to find our y-value.

Put this in your calculator now: -16(1/2)2+16(1/2)+30

14

Multiple Choice

What is the y-value of the vertex?

1

1/2

2

-34

3

34

4

75

15

The ordered pair of the vertex is at (1/2, 34).

*Remember, our x values are t (time) in this function. Our y values are h (height).​

This means that the diver reached the highest point of the dive, 34 feet (h), at 1/2 second (t).​

He started at 30 feet, so subtracting 34-30 puts him at 4 feet above the platform.​

16

Try It!​

  1. We will plug in 20 as his initial height and 8 as his initial velocity.

    h(t) = -16t2+8t+20

This time, use desmos.com to graph this function and find his maximum height.

Go on, I'll wait...​

17

Multiple Choice

What was the vertex of the equation h(t) = -16t2+8t+20?

1

(0, 20)

2

(1.4, 0)

3

(-0.9, 0)

4

(0.25, 21)

18

Since the vertex is at (0.25, 21) and our y-value represents height, then the Diver's maximum height is 21 feet.

19

Example 3

Just some reminders:

  • A residual is the result of the (actual y - predicted y​).

  • The actual y-value comes from the data.

  • The predicted y-value comes from the best fit function.

  • A residual plot shows a good fit if the points are random and do not form a pattern. ​

Subject | Subject

Some text here about the topic of discussion

20

Take a few minutes to finish graphing the actual data for Example 3. These points form a quadratic pattern. That's why the best fit function is a quadratic function.

Now, find the residuals by completing the second table. Graph the residuals to create a residual plot.​

21

Example 4

Just like we can run a linear regression to find the line of best fit, we can run a quadratic regression when our data shows a quadratic pattern.

Go to STAT: Edit: Put your x values (price increase) as L1 and your y values (average revenue) as L2.

22

Does your screen look like this?

​L

​L

​0

​745

​1

​846

​2

​910

​3

​952

​4

​1008

23

  • Make sure you have Diagnostics on: Mode: STAT DIAGNOSTICS: ON

  • STAT: CALC: 5 (QuadReg): Enter

  • Go down to calculate and hit enter again​

    • a = the a value of your quadratic best fit function

    • b = the b value of your quadratic best fit function

    • c = the c value of your quadratic best fit function

    • r2 tells you if the regression is a good fit. You want your r2 value to be close to 1.​

24

Multiple Select

What is the quadratic function of best fit for this data and is it a good fit?

1

ax2+bx+c

2

-8+95.2+749.8

3

-8x2+95.2x+749.8

4

Yes; r2 = 0.99 which is close to 1

5

No; r2 = 0.99 which is not close to 1

25

Now to answer the question on the paper...

If the price goes up one more time, our new x-value will be 5. Put your new function -8x2+95.2x+749.8 into y= and find y when x = 5.

The predicted value of y = 1025.8, meaning the revenue would be $1025.80. That means the revenue will continue to go up if prices are increased one more time. ​

26

Try it!

  1. Stay in the table that you just used to answer the last question. Find y when x=6 and when x=7

What do you notice?

​x

​y

​6

​1033

​7

​1024.2

27

The revenue continued to increase with the 6th price increase, from $1025.80 to $1033. However, after the 7th price increase, the revenue started going down, to $1024.20.

(What this means is that people will stop buying tickets once the price goes up so many times. Less tickets = less revenue)​

28

Here's what we learned today...

  • Area: When the length and width are represented by variable expressions, area will be represented by a quadratic function.

  • Vertical Motion: The constant value in the vertical motion model gives us the initial height of the object.

  • Data: We can use quadratic regression to find the best fit function for a set of quadratic data. A good fit means the r2 value will be close to 1.​

29

What's next???

  • Make sure you have all your notes filled out.

  • In Google classroom, go to the section "Savvas Topic Practice". Click on the assignment labeled "Topic 8-4 Practice" and complete.

Lesson 8-4 Modeling with Quadratic Functions

By Laura Wroten

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