Distracted Driving
Algebra I Lesson
Lesson Title: Distracted Driving and Linear Regression
Primary Author: Justin Field, Chesapeake High School, Baltimore County Public Schools
Peer Reviewed and Revised By: Arra Chung, Overlea High School, Baltimore County Public Schools
Background Information
Subject:
Identify the course the unit will be
implemented in.
Algebra I (Or Unit 3 of Algebra 2) (data appears to actually be quadratic, although it is
appropriate to begin by performing a linear regression and plotting the residual values in
order to draw that conclusion.
Grade Band:
Identify the appropriate grade band for
the lesson.
9-12
Duration:
45 – 90 minutes
Identify the time frame for the unit.
Overview:
Provide a concise summary of what students
will learn in the lesson. It explains the unit’s
focus, connection to content, and real world
connection.
STEM Specialist Connection:
Describe how a STEM Specialist may be
used to enhance the learning experience.
STEM Specialist may be found at
http://www.thestemnet.com/
Students will explore the real-world problem of distracted driving by analyzing the
relationship between auto accident fatalities over time and auto accident fatalities over time
due to distracted driving for the years 2005-2009. Students will create scatter plots and
linear regression equations as well as analyze their results. Students will interpret the
meaning of the slope, y-intercept, correlation coefficient, and graphs of the residual values
in the context of the accident and distracted driving data. Student will use data to support or
refute that claim that distracted driving increases the amount of fatal accidents.
A STEM Specialist may be used to in a variety of ways in this lesson. Listed below are
some suggestions:
1. Engagement – The STEM Specialist can be used to engage students in hands-on
activities that demonstrate how statistics can be used to predict future outcomes.
2. Exploration – The STEM Specialist can assist students in developing and analyzing
graphs.
Enduring Understanding:
Identify discrete facts or skills to focus on
larger concepts, principles, or processes.
They are transferable - applicable to new
situations within or beyond the subject.
Statistics can be used to provide a measure of probability of observing certain outcomes.
This lesson was developed through a collaboration with the Maryland Business Roundtable for Education and the Maryland State
Department of Education Office of STEM Initiatives.
Page 1 of 19
Distracted Driving
Algebra I Lesson
Background Information
Essential Questions:
Identify several open-ended questions to
provoke inquiry about the core ideas for the
lesson. They are grade-level appropriate
questions that prompt intellectual exploration
of a topic.
Student Outcomes:
Identify the transferable knowledge and skills
that students should understand and be able
to do when the lesson is completed.
Outcomes must align with but not limited to
Maryland State Curriculum and/or national
standards.
Product, Process, Action,
Performance, etc.:
Identify what students will produce to
demonstrate that they have met the
challenge, learned content, and
employed 21st century skills. Additionally,
identify the audience they will present
what they have produced to.
How are statistics used to support the dangers of distracted driving ?
Students will be able to:
● graph a linear regression line.
● create a scatter plot.
● find the linear regression to interpret data and make predictions.
● interpret the meaning of a graph of residual values given a regression equation for a
set of data.
● develop an argument using data to support or refute a claim.
Audience:
☐Peers
☐Experts / Practitioners
Students will construct an argument to support or refute the
☒Teacher(s)
claim that distracted driving increases the amount of fatal
accidents. Students will use data to support their argument.
☐School Community
☐Online Community
☐Other______
Maryland Common Core State Algebra I Curriculum Framework:
Standards Addressed in the Unit:
Identify the Maryland State Curriculum
Standards and/or national standards
addressed in the unit.
A.CED.2 Create equations in two or more variables to represent relationships between
quantities; graph equations on coordinate axes with labels and scales.
A.REI.1 Explain each step in solving a simple equation as following from the equality of
numbers asserted at the previous step, starting from the assumption that the original
equation has a solution. Construct a viable argument to justify a solution method.
A.REI.10 Understand that the graph of an equation in two variables is the set of all its
solutions plotted in the coordinate plane, often forming a curve (which could be a line).
This lesson was developed through a collaboration with the Maryland Business Roundtable for Education and the Maryland State
Department of Education Office of STEM Initiatives.
Page 2 of 19
Distracted Driving
Algebra I Lesson
Background Information
F.IF.4 For a function that models a relationship between two quantities, interpret key
features of the graph and the table in terms of the quantities, and sketch the graph showing
key features given a verbal description of the relationship. Key features include: intercepts;
intervals where the function is increasing, decreasing, positive, or negative; relative
maximums and minimums; symmetries; end behavior; and periodicity.
S.ID.6 Represent data on two quantitative variables on a scatter plot, and describe how the
variables are related.
a. Fit a function to the data; use functions fitted to data to solve problems in the context
of the data. Use given functions
or choose a function suggested by the context. Emphasize linear and exponential
models.
b. Informally assess the fit of a function by plotting and analyzing residuals
S.ID7 Interpret the slope (rate of change) and the intercept (constant term) of a linear model
in the context of the data
S.ID8 Compute (using technology) and interpret the correlation coefficient of a linear fit
Maryland Common Core State Curriculum Framework Reading Standards for
Literacy in Science and Technical Subjects
RST.9-10.7 Translate quantitative or technical information expressed in words in a text into
visual form (e.g., table or chart) and translate information expressed visually or
mathematically (e.g., in an equation) into words.
Maryland Common Core State Curriculum Framework Standards for Writing in
Science and Technical Subjects
WHST.9.10.1 Write arguments focused on discipline-specific content.
This lesson was developed through a collaboration with the Maryland Business Roundtable for Education and the Maryland State
Department of Education Office of STEM Initiatives.
Page 3 of 19
Distracted Driving
Algebra I Lesson
Background Information
Equipment:
 TI Graphing Calculators
 Computer connected to a projector
Websites*:
 Data in the handout was retrieved from: http://www.distraction.gov/research/pdffiles/distracted-driving-2009.pdf (Page 2 chart)
 Engagement Video:
http://www.youtube.com/watch?v=nR82z0tzMdc
Suggested Materials and
Resources:
Identify materials needed to complete the
unit. This includes but is not limited to
websites, equipment, PowerPoints, rubrics,
worksheets, and answer keys.
Alternate Video Websites:
 http://www.youtube.com/watch?feature=player_embedded&v=fbiHwGBsRr0
Have students explain what happened when the participants drove normally verses
when they were texting or under the influence of alcohol. What did the video identify
as making these distractions so dangerous?
 http://www.youtube.com/watch?feature=player_embedded&v=K2D3hB278Gc
Ask the students what makes it difficult to follow the rule of not texting while driving
seeing the harsh consequences and results that can occur?
Additional Information on Distracted Driving
 http://www.infographicsshowcase.com/teen-driving-distractions/
Flyer on teenagers driving distracted
 http://www.tnonline.com/2013/feb/27/texting-and-driving-statistics
Texting and Driving Statistics
 http://www.edgarsnyder.com/car-accident/cell-phone/cell-phone-statistics.html
Article on cell phone and driving statistics
 http://www.census.gov/compendia/statab/2012/tables/12s1114.pdf
Data on types of crashes in 2009
* Throughout the lesson, students are linked to online resources in order to conduct research. The sites have been chosen
for their content and grade-level appropriateness. Teachers should preview all websites before introducing the activities to
students and adhere to their school system’s policy for internet use.
This lesson was developed through a collaboration with the Maryland Business Roundtable for Education and the Maryland State
Department of Education Office of STEM Initiatives.
Page 4 of 19
Distracted Driving
Algebra I Lesson
Background Information
People, Facilities:
STEM Specialist – Algebra
Materials (rubrics, worksheets, PowerPoints, answer keys, etc.):
Student Resources:
1. Distracted Driving Linear Regression
2. Calculator Notes on Linear Regression
Teacher Resources:
1. Distracted Driving Linear Regression Answer Key
2. Suggested Argumentative Writing Rubric http://www.schoolimprovement.com/docs/Common%20Core%20Rubrics_Gr9-10.pdf
This lesson was developed through a collaboration with the Maryland Business Roundtable for Education and the Maryland State
Department of Education Office of STEM Initiatives.
Page 5 of 19
Distracted Driving
Algebra I Lesson
Learning Experience
5E Component
Identify the 5E
component addressed
for the learning
experience. The 5E
model is not linear.
☒Engagement
☐Exploration
Details
Materials:


Computer connected to a projector.
Cell phone.
☐Explanation
Preparation:
☐Extension
☐Evaluation
Have video loaded and ready to play.
http://www.youtube.com/watch?v=nR82z0tzMdc
Facilitation of Learning Experience:
Prior to class, ask a student to send a text to another student at the beginning of
the class. When you see the student looking at his/her phone, make a simple
comment or question, and then call on that student for a response.
Follow with a brief discussion on how quickly a person get can get distracted and
then have the class watch the video:
http://www.youtube.com/watch?v=nR82z0tzMdc
Standards for
Mathematical Practices
☐Make sense of
problems and
persevere in solving
them.
☐Reason abstractly and
quantitatively.
☐Construct viable
arguments and critique
the reasoning of
others.
☐Model with
mathematics
☐Use appropriate tools
strategically
☐Attend to precision.
☐Look for and make use
of structure.
☐Look for and express
regularity in repeated
reasoning.
This lesson was developed through a collaboration with the Maryland Business Roundtable for Education and the Maryland State
Department of Education Office of STEM Initiatives.
Page 6 of 19
Distracted Driving
Algebra I Lesson
Learning Experience
5E Component
Identify the 5E
component addressed
for the learning
experience. The 5E
model is not linear.
☐Engagement
☒Exploration
☐Explanation
☐Extension
☐Evaluation
Details
Standards for
Mathematical Practices
Materials:



TI Graphing Calculators
Student Resource 1: Distracted Driving Linear Regression
Student Resource 2: Calculator Notes on Linear Regression
Preparation:
Make copies of the handouts for students. You may provide students all
the handouts at once or allow students to complete one sheet then provide
them with the next.
☐Make sense of
problems and
persevere in solving
them.
☐Reason abstractly and
quantitatively.
☐Construct viable
arguments and critique
Facilitation of Learning Experience:
the reasoning of
others.
Provide students with copies of the Distracted Driving Linear Regression Handout
☐Model with
Students will think, write, and share their responses to the following question:
mathematics
What are some ways/tools that can distract drivers on the road? How does it
☒Use appropriate tools
affect how a person drives?
strategically
Finding the Linear Regression Line
☒Attend to precision.
Teachers please remind students to turn on the diagnostics so the
correlation coefficient is displayed when determining the line of regression
☒Look for and make use
of structure.
Students will use graphing calculators to calculate the linear regression of fatal
accident due to distracted driving. Provide guidance to students as they work
through the problems in the handout.
☐Look for and express
regularity in repeated
reasoning.
Student Resource 2: Calculator Notes on Linear Regression
This lesson was developed through a collaboration with the Maryland Business Roundtable for Education and the Maryland State
Department of Education Office of STEM Initiatives.
Page 7 of 19
Distracted Driving
Algebra I Lesson
Learning Experience
5E Component
Identify the 5E
component addressed
for the learning
experience. The 5E
model is not linear.
☐Engagement
☐Exploration
☒Explanation
☐Extension
☐Evaluation
Details
Materials:


Student Resource 1: Distracted Driving Linear Regression
Student Resource 2: Calculator Notes on Linear Regression
Facilitation of Learning Experience:
Analysis of the Data
After students have completed the graphs and analysis of the two situations, they
should individually answer questions within the summary portion of the lesson in
preparation for a class discussion of their answer (If needed, provide students
with the calculator notes on how to determine the line of regression using a
calculator).
Standards for
Mathematical Practices
☐Make sense of
problems and
persevere in solving
them.
☒Reason abstractly and
quantitatively.
☒Construct viable
arguments and critique
the reasoning of
others.
☐Model with
mathematics
☐Use appropriate tools
strategically
☐Attend to precision.
☐Look for and make use
of structure.
☐Look for and express
regularity in repeated
reasoning.
This lesson was developed through a collaboration with the Maryland Business Roundtable for Education and the Maryland State
Department of Education Office of STEM Initiatives.
Page 8 of 19
Distracted Driving
Algebra I Lesson
Learning Experience
5E Component
Identify the 5E
component addressed
for the learning
experience. The 5E
model is not linear.
☐Engagement
☐Exploration
☐Explanation
Details
Materials:


Teacher Resource 1: Distracted Driving Linear Regression Answer Key
Teacher Resource 2: Suggested Argumentative Writing Rubric http://www.schoolimprovement.com/docs/Common%20Core%20Rubrics_
Gr9-10.pdf
☐Extension
Facilitation of Learning Experience:
☒Evaluation
Use the answer key to evaluate answers.
Teacher Resource 1: Distracted Driving Linear Regression Answer Key
The argumentative writing rubric may be use to assess question six, “Construct
an argument to support or refute the claim that distracted driving increase the
amount of fatal accidents. Use data to support your argument.”
Alternative activities include having students do oral presentations or developing
public service announcements to raise awareness about the dangers of
distracted driving.
Standards for
Mathematical Practices
☐Make sense of
problems and
persevere in solving
them.
☐Reason abstractly and
quantitatively.
☐Construct viable
arguments and critique
the reasoning of
others.
☐Model with
mathematics
☐Use appropriate tools
strategically
☐Attend to precision.
☐Look for and make use
of structure.
☐Look for and express
regularity in repeated
reasoning.
This lesson was developed through a collaboration with the Maryland Business Roundtable for Education and the Maryland State
Department of Education Office of STEM Initiatives.
Page 9 of 19
Distracted Driving
Algebra I Lesson
Learning Experience
5E Component
Identify the 5E
component addressed
for the learning
experience. The 5E
model is not linear.
☐Engagement
Details
Materials:
Teacher Resource 1: Distracted Driving Linear Regression Answer Key
☐Exploration
☐Explanation
Facilitation of Learning Experience:
☐Make sense of
problems and
persevere in solving
them.
Residual Plots
☐Reason abstractly and
quantitatively.
Haves students complete the residual plots question on their worksheet.
☒Construct viable
arguments and critique
the reasoning of
others.
☒Extension
☐Evaluation
Standards for
Mathematical Practices
☐Model with
mathematics
☐Use appropriate tools
strategically
☐Attend to precision.
☐Look for and make use
of structure.
☐Look for and express
regularity in repeated
reasoning.
This lesson was developed through a collaboration with the Maryland Business Roundtable for Education and the Maryland State
Department of Education Office of STEM Initiatives.
Page 10 of 19
Algebra I
Name:
Distracted Driving and Fatal Car Crash Linear Regression
Directions: Write your response to the questions below in the space given below.
What are some ways/tools that can distract drivers on the road? How does it
affect how a person drives?
Directions:
1. Fatal Accidents by Year
1. Plot the data on the graph to the right
2. Graph the line of best fit on the scatter plot to the right.
3. Determine the linear regression and calculate the r2 coefficient.
Equation: ______________________________
r2:_______
4.
Using your equation how many accidents due to distractions will
there be in 2014?
5.
What does the correlation coefficient reveal about how well the
regression line fits the data?
6.
What is the general trend in the number of accidents due to
distractions per year?
7.
In what year would there be 25,000 accidents due to
distractions?
Directions:
2. Fatal Accidents by Year Due to Distractions
1. Plot the data on the graph to the right
2. Graph the line of best fit on the scatter plot to the right.
3. Determine the linear regression and calculate the r2 coefficient.
Equation: ______________________________
r2:_______
4.
Using your equation how many accidents due to distractions
will there be in 2014?
5.
What does the correlation coefficient reveal about how well the
regression line fits the data?
6.
What is the general trend in the number of accidents due to
distractions per year?
7.
In what year would there be 2,000 accidents due to
distractions?
Year since
2005
0
1
2
3
4
Year
0
1
2
3
4
Year since
2005
0
1
2
3
4
Year
0
1
2
3
4
Fatal
Accidents
39,252
38,648
37,435
34,172
30,797
Accidents
39,252
38,648
37,435
34,172
30,797
Fatal
Accidents
4,026
5,245
5,329
5,307
4,898
Accidents
4,026
5,245
5,329
5,307
4,898
Analyzing the Data
1. Examine the linear regression equation in situation 1. What do the slope and y intercept
represent in the context of the data?
2. What does the model predict for the number of accidents in 2013?
3. What does the model predict for the number of accidents in 1990?
4. Examine the linear regression equation in situation 2. What do the slope and y intercept
represent in the context of the data?
5. Does the model’s prediction for the number of accidents in 1990 make sense? (What
technology was available to distract driver’s from 2005-2009 that was not available in 1990?)
6. On a separate sheet of paper, construct an argument to support or refute the claim that
distracted driving increase the amount of fatal accidents. Use data to support your argument.
Residual Plots
Examining the residual plots for the two data sets, what conclusions can you draw about how
well the linear models fit the data?
Residuals for Situation 1
Residuals for Situation 2
Algebra I
Name:
Distracted Driving and Fatal Car Crash Linear Regression Answer Key
Directions: Write your response to the questions below in the space given below.
What are some ways/tools that can distract drivers on the road? How does it
affect how a person drives?
Answers will vary




Drinking
Eating
Putting make up on
Using cell phones
Answers will vary




Accidents
Death
Paralysis
Driving outside of the lanes
Directions:
1. Fatal Accidents by Year
1. Plot the data on the graph to the right
2. Graph the line of best fit on the scatter plot to the right.
3. Determine the linear regression and calculate the r2 coefficient.
Equation: __ y = .2138.6x + 40338 _________
r2:_0.91____
4.
Using your equation how many accidents due to distractions will
there be in 2014?
21090.6 fatal accidents
5. What does the correlation coefficient reveal about how well the
regression line fits the data?
Year since
2005
0
1
2
3
4
Year
0
1
2
3
4
Fatal
Accidents
39,252
38,648
37,435
34,172
30,797
Accidents
39,252
38,648
37,435
34,172
30,797
There is a strong positive linear correlation
6.
What is the general trend in the number of accidents due to
distractions per year?
The number of accidents decrease
7. In what year would there be 25,000 accidents due to
distractions?
Year 7 - 2012
Directions:
2. Fatal Accidents by Year Due to Distractions
1. Plot the data on the graph to the right
2. Graph the line of best fit on the scatter plot to the right.
3. Determine the linear regression and calculate the r2 coefficient.
Equation: ___ y = 180.6x + 4599.8___________
0.27_____
r2:__
4.
Using your equation how many accidents due to distractions
will there be in 2014?
6225.2 fatal accidents
5. What does the correlation coefficient reveal about how well the
regression line fits the data?
There is a weak positive linear correlation
6.
7.
What is the general trend in the number of accidents due to
distractions per year?
The number of accidents increase
In what year would there be 2,000 accidents due to
distractions?
Year 14 - 2019
Year since
2005
0
1
2
3
4
Year
0
1
2
3
4
Fatal
Accidents
4,026
5,245
5,329
5,307
4,898
Accidents
4,026
5,245
5,329
5,307
4,898
Analyzing the Data
1. Examine the linear regression equation in situation 1. What do the slope and y intercept
represent in the context of the data?
Slope: The number of fatal accidents decreases by about 2138 each year.
Y-Intercept: The number of fatal accidents in 2005 was 39,252.
2. What does the model predict for the number of accidents in 2013?
Y = -2138.6 (8) + 40338 = 23229.2 fatal accidents
3. What does the model predict for the number of accidents in 1990?
Y = -2138.6 (-15) + 40338 = 72467 fatal accidents
4. Examine the linear regression equation in situation 2. What do the slope and y intercept
represent in the context of the data?
Slope: The number of fatal accidents caused by distraction increases by 180 each year.
Y-Intercept: The number of fatal accidents caused by distractions in 2005 was 4026.
5. Does the model’s prediction for the number of accidents in 1990 make sense? (What
technology was available to distract driver’s from 2005-2009 that was not available in 1990?)
Answers may vary - Yes because based on the linear regression line, there were
about 1891 fatal accidents caused by distractions which are smaller than the
number of accidents that are stated in the table.
Tablets, i-pods, mp3s, etc.
6. On a separate sheet of paper, construct an argument to support or refute the claim that
distracted driving increase the amount of fatal accidents. Use data to support your argument.
Answers will vary
Residual Plots
1. Examining the residual plots for the two data sets, what conclusions can you draw about how
well the linear models fit the data?
Residuals for Situation 1
Supports a linear model
Residuals for Situation 2
Supports a non-linear model