# MAFS.8.SP.1.1

Construct and interpret scatter plots for bivariate measurement data to investigate patterns of association between two quantities. Describe patterns such as clustering, outliers, positive or negative association, linear association, and nonlinear association.
General Information
Subject Area: Mathematics
Domain-Subdomain: Statistics & Probability
Cluster: Level 2: Basic Application of Skills & Concepts
Cluster: Investigate patterns of association in bivariate data. (Supporting Cluster) -

Clusters should not be sorted from Major to Supporting and then taught in that order. To do so would strip the coherence of the mathematical ideas and miss the opportunity to enhance the major work of the grade with the supporting clusters.

Date of Last Rating: 02/14
Status: State Board Approved
Assessed: Yes
Test Item Specifications

• Assessment Limits :

Numbers in items must be rational numbers.

• Calculator :

Neutral

• Context :

Allowable

Sample Test Items (2)
• Test Item #: Sample Item 1
• Question:

A scatter plot is shown for bottled water sales and temperature. Select all statements that correctly interpret the graph.

• Difficulty: N/A
• Type: MS: Multiselect

• Test Item #: Sample Item 2
• Question:

A scatter plot is shown. Which statement is true for the scatter plot?

• Difficulty: N/A
• Type: MC: Multiple Choice

## Related Courses

This benchmark is part of these courses.
1205050: M/J Accelerated Mathematics Grade 7 (Specifically in versions: 2014 - 2015, 2015 - 2020, 2020 - 2022 (current), 2022 and beyond)
1205070: M/J Grade 8 Pre-Algebra (Specifically in versions: 2014 - 2015, 2015 - 2022 (current), 2022 and beyond)
1204000: M/J Foundational Skills in Mathematics 6-8 (Specifically in versions: 2014 - 2015, 2015 - 2022 (current), 2022 and beyond)
7812030: Access M/J Grade 8 Pre-Algebra (Specifically in versions: 2014 - 2015, 2015 - 2018, 2018 - 2019, 2019 and beyond (current))

## Related Access Points

Alternate version of this benchmark for students with significant cognitive disabilities.
MAFS.8.SP.1.AP.1a: Graph data using line graphs, histograms or box plots.
MAFS.8.SP.1.AP.1b: Graph bivariate data using scatter plots and identify possible associations between the variables.
MAFS.8.SP.1.AP.1c: Using box plots and scatter plots, identify data points that appear to be outliers.

## Related Resources

Vetted resources educators can use to teach the concepts and skills in this benchmark.

## 3D Modeling

Wind Farm Design Challenge:

This  lesson is a problem-based learning activity aligned to Florida's math and science standards. In this middle-school engineering design challenge, students are asked to create the most efficient wind turbine while balancing cost constraints. Students will apply their knowledge of surface area and graphing while testing 3D-printed wind farm blades. In the end, students are challenged to design and test their own wind farm blades, using Tinkercad to model a 3D-printable blade.

Type: 3D Modeling

## Assessments

Sample 4 - Eighth Grade Math State Interim Assessment:

This is a State Interim Assessment for eighth grade.

Type: Assessment

Sample 3 - Eighth Grade Math State Interim Assessment:

This is a State Interim Assessment for eighth grade.

Type: Assessment

Sample 2 - Eighth Grade Math State Interim Assessment:

This is a State Interim Assessment for eighth grade.

Type: Assessment

Sample 1 - Eighth Grade Math State Interim Assessment:

This is a State Interim Assessment for eighth grade.

Type: Assessment

## Formative Assessments

Sleepy Statistics:

Students are given a scatter plot in a real-world context and asked to describe the association between the variables.

Type: Formative Assessment

Population Density:

Students are given a scatterplot in a real-world context and asked to describe the association between the variables.

Type: Formative Assessment

Infectious Statistics:

Students are given a scatterplot in a real-world context and asked to describe the association between the variables.

Type: Formative Assessment

Cheesy Statistics:

Students are given a scatterplot in a real-world context and asked to describe the association between the variables.

Type: Formative Assessment

Bungee Cord Data:

Students are asked to construct a scatterplot corresponding to a given set of data.

Type: Formative Assessment

## Lesson Plans

Sea Turtle Nesting Associations:

In this lesson, students preview a Sea Turtle Research Perspectives Video to introduce the idea that sea turtle gender hatching rates and temperature are related. Students will use scatterplots to visualize the relationships and draw conclusions about associations and how it helps in interpreting two variable data sets.

Type: Lesson Plan

Clean Up, Collect Data, and Conserve the Environment!:

Students will explore the use of mean and median in finding the ratio of a set of data. They will collect this set of data by doing a trash pick-up service learning project and then weighing the weight of the trash collected in bags. The students will discuss the use of mean and median in finding the relationship between the independent and dependent variables of the data collected. They will also look at the positive and negative correlations of this relationship, as displayed on a scatter plot they created. In comparison, they will then look at the data collected from the coastal cleanup report and compare this with their own data. Finally, students will use the data to help determine interventions at the local, state and national level regarding environmental issues.

Type: Lesson Plan

The changing climate is an important topic for both scientific analysis and worldly knowledge. This lesson uses data collected by the National Snow and Ice Data Center to create and use mathematical models as a predictive tool and do critical analysis of sea ice loss.

Type: Lesson Plan

Sensoring Data:

In this follow up lesson, students will explore data collection using the weather station sensor and perform statistical analysis of the data. Students will use a scientific method of inquiry to plan an investigation of their own. This activity is meant to allow students to use a variety of skills they have acquired throughout a statistics unit in a personally meaningful way.

Type: Lesson Plan

In this design challenge, students will explore electrical circuits. Students will use their skills in science, math, and technology to determine how many light bulbs can be powered off of one circuit. Students will build circuits, measure luminosity, graph data, analyze the data and then report their findings to Kiser construction.

Type: Lesson Plan

Shipwrecked Pirates:

In this lesson, students will take the role of shipwrecked pirates. Working in groups, they will have to use the concepts of force, speed, scatter plots, and literal equations to come up with a way of getting one student to a nearby sister island so that they will both have enough food to survive.

Type: Lesson Plan

Mixtures and Solutions Uncovered:

This lesson is a hands-on approach to SC.8.P.8.9 that the students enjoy and are engaged in. The main activities cover making anchor charts (teacher lead) that will assist them in completing activities that cover vocabulary and a break down of characteristics for mixtures. There are four group activities that will guide the students to an understanding of the standard outlined. This is a two-day lab that adds teacher demonstration and allows for collaborative group and student-talk sessions.

Type: Lesson Plan

Sensoring Data:

In this follow up lesson, students will explore data collection using the weather station sensor and perform statistical analysis of the data. Students will use a scientific method of inquiry to plan an investigation of their own. This activity is meant to allow students to use a variety of skills they have acquired throughout a statistics unit in a personally meaningful way.

Type: Lesson Plan

Height Arm Juxtaposition:

This lesson is a Follow Up Activity to the Algebra Institute and allows students to apply their skills on analyzing bivariate data. This STEM lesson allows students the opportunity to investigate if there is a linear relationship between a person's height and arm length. Using technology the students will explore in-depth how to perform a least square regression as a procedure for determining the line of best fit.

Type: Lesson Plan

Height Scatterplot Lab:

This lesson is a Follow Up Activity to the Algebra Institute and allows students to apply their skills on analyzing bivariate data. This STEM lesson allows students the opportunity to investigate if there is a linear relationship between a person's height and foot length. Using technology the students can determine the line of best fit, correlation coefficient and use the line for interpolation.

Type: Lesson Plan

Star Scatter Plots:

In this lesson, students plot temperature and luminosity data from a provided star table to create a scatter plot. They will analyze the data to sequence the colors of stars from hottest to coolest and to describe the relationship between temperature and luminosity. This lesson does not address differentiation between absolute and apparent magnitude.

Type: Lesson Plan

Text Count and Homework Minutes:

Text Count and Homework Minutes

The Students will engage in counting Text minutes and Homework minutes. They will keep a journal to be kept over a four day period, Monday thru Thursday. The assignment can be done on Friday. The students will record the number of text messages received and sent out during the hours of 3:00-11:00. On the second journal the students will also record the number of minutes spent on homework between the hours of 3:00-11:00. They will compile this information into graphs on that 5th day Friday. With this data the students will be able to plot a scatter plot graph and learn how to recognize patterns on a scatter plot graph. Students will see the relevance of a correlation even if the graph is not linear or a straight line. Students will identify trends and articulate the reason for the trends.

Type: Lesson Plan

Scattered Time:

Through a slide show presentation, students will be led through data in one variable, bivariate data, scatter plots, lines of best fit, outliers, and correlations. They will be able to analyze bivariate data to determine correlations, associations, and the impact of outliers.

Type: Lesson Plan

Scatter Plots at Arm's Reach:

This lesson is an introductory lesson to scatter plots and line of best fit (trend lines). Students will be using m&m's to represent different associations in scatter plots, and measure each other's height and arm span to create their own bivariate data to analyze. Students will be describing the association of the data, patterns of the data, informally draw a line of best fit (trend line), write the equation of the trend line, interpret the slope and y-intercept, and make predictions.

Type: Lesson Plan

Help, My Data is Scattered!!!:

This lesson provides activities for students to conceptually understand how to gather, organize, and interpret data using a scatter plot. They will be required to work cooperatively to complete certain tasks. They will use estimation strategies to complete a experiment that compares the the length of their hand to the number of centimeter cubes they can grab in order to make predictions about data with a larger sample size. Students will be assessed formally and informally throughout lesson via slide notes and data collection tool.

Type: Lesson Plan

Where do I fit in?:

Students will do an exploration activity with paper airplanes. They will be up and moving around. Students will be able to understand and analyze bivariate data that they will be able to plot from the exploration activity. They will be able to describe patterns, and also find facts and come up with conclusions based on the data they gather.

Type: Lesson Plan

What's Your Association: Scatter Plots and Bivariate Data:

In this lesson, students will learn how to graph, describe, and determine patterns and associations for bivariate data. This lesson incorporates vocabulary development and collaboration.

Type: Lesson Plan

This lesson will get your student up to speed with constructing and interpreting scatter plots using bivariate data. With this lesson, patterns of association are investigated between two quantities and positive or negative association as well as linear and non-linear association is determined through the use of data from the NFL as reported by ESPN. Data from Consumer Reports is used to determine associations between shoe price and quality.

Type: Lesson Plan

Chemical or Physical Change? That is the Question!:

Students will conduct an investigation on the effect of laundry detergent on water temperature, use technology to graph their data, and determine whether a physical or chemical change occurred. Students will also read articles to gather evidence to write an evidence-based claim using the CLEVER method.

Type: Lesson Plan

How Fast Can You Go:

Students will apply skills (making a scatter plot, finding Line of Best Fit, finding an equation and predicting the y-value of a point on the line given its x-coordinate) to a fuel efficiency problem and then consider other factors such as color, style, and horsepower when designing a new coupe vehicle.

Type: Lesson Plan

Scattered Data:

This lesson allows students to use real-life problem-solving skills to construct and interpret scatter plots by generating and recording their own data. Students will investigate patterns between bivariate measurement data. They will model linear associations with a line of best fit.

Type: Lesson Plan

Spaghetti Bridges:

Students use data collection from their spaghetti bridge activity to write linear equations, graph the data, and interpret the data.

Type: Lesson Plan

Finding the Hottest Trend:

In this lesson, students will plot a scatter plot graph and learn how to recognize patterns on a scatter plot graph. The students will realize that even though the points are not in a straight line (linear function), a correlation may still exist. Students will be able to find and describe trends, and justify their reasoning.

Type: Lesson Plan

Guess the Celebrities' Heights!:

In this activity, students will use scatter plots to compare estimated and actual heights of familiar celebrities and athletes. They will determine how their answers impacted the correlation of their data, including the influence of outliers. Finally, they will compare their correlation to that provided in a scatter plot with a larger data sample.

Type: Lesson Plan

## Original Student Tutorials

The Notion of Motion, Part 3 - Average Velocity:

Describe the average velocity of a dune buggy using kinematics in this interactive tutorial. You'll calculate displacement and average velocity, create and analyze a velocity vs. time scatterplot, and relate average velocity to the slope of position vs. time scatterplots.

This is part 3 of 3 in a series that mirrors inquiry-based, hands-on activities from our popular workshops.

• Click  to open The Notion of Motion, Part 1 - Time Measurements
• Click HERE to open The Notion of Motion, Part 2 - Position vs Time

Type: Original Student Tutorial

The Notion of Motion, Part 2 - Position vs Time:

Continue an exploration of kinematics to describe linear motion by focusing on position-time measurements from the motion trial in part 1. In this interactive tutorial, you'll identify position measurements from the spark tape, analyze a scatterplot of the position-time data, calculate and interpret slope on the position-time graph, and make inferences about the dune buggy’s average speed

Type: Original Student Tutorial

Scatterplots Part 2: Patterns, Associations and Correlations:

Explore the different types of associations that can exist between bivariate data in this interactive tutorial.

This is part 2 in 6-part series. Click below to open the other tutorials in the series.

Type: Original Student Tutorial

Scatterplots Part 1: Graphing:

Learn how to graph bivariate data in a scatterplot in this interactive tutorial.

This is part 1 in 6-part series. Click below to open the other tutorials in the series.

Type: Original Student Tutorial

## Perspectives Video: Expert

Birdsong Series: Statistical Analysis of Birdsong:

Wei Wu discusses his statistical contributions to the Birdsong project which help to quantify the differences in the changes of the zebra finch's song.

Type: Perspectives Video: Expert

## Perspectives Video: Professional/Enthusiasts

Determining Strengths of Shark Models based on Scatterplots and Regression:

Chip Cotton, fishery biologist, discusses his use of mathematical regression modeling and how well the data fits his models based on  his deep sea shark research.

Type: Perspectives Video: Professional/Enthusiast

Asymptotic Behavior in Shark Growth Research:

Fishery Scientist from Florida State University discusses his new research in deep sea sharks and the unusual behavior that is found when the data is graphed.

Type: Perspectives Video: Professional/Enthusiast

Slope and Deep Sea Sharks:

Shark researcher, Chip Cotton, discusses the use of regression lines, slope, and determining the strength of the models he uses in his research.

Type: Perspectives Video: Professional/Enthusiast

You and Michael:

In this problem solving task, students will test Marcus Vitruvius"s theory that a person"s height is approximately equal to their arm span (wingspan). Students will test this theory via collection, recording, graphing and analysis of data.

Bear Hugs:

In this problem solving activity, students are tasked with measuring the arm lengths of fellow students. Students will record the data and use it to construct a boxplot and scatterplot to help draw conclusions.

How Is the Weather?:

This task can be used as a quick assessment to see if students can make sense of a graph in the context of a real world situation. Students also have to pay attention to the scale on the vertical axis to find the correct match. The first and third graphs look very similar at first glance, but the function values are very different since the scales on the vertical axes are very different. The task could also be used to generate a group discussion on interpreting functions given by graphs.

Students are asked to examine a scatter plot and then interpret its meaning. Students should identify the form of the relationship (linear, curved, etc.), the direction or correlation (positive or negative), any specific outliers, the strength of the relationship between the two variables, and any other relevant observations.

## Professional Development

What Does It Mean To Measure?:

This is a professional development session from the Learning Math series from Annenberg. Learners will begin to explore the questions "What can be measured?" and "What does it mean to measure something?" Learners identify measurable properties of objects such as weight, surface area, and volume, and discuss which metric units are appropriate for measuring these properties. Learners will also learn that measurement is, by its nature, approximate. Finally, learners will consider how to make measurements using nonstandard units. This session features a number of problems for learners to solve and open-ended questions to discuss, videos that demonstrate measurement techniques, and an interactive activity that asks learners to construct shapes using different size triangles to foster understanding of area and perimeter. There are also nine homework problems in which learners are asked to generate different measurements, graph measurements, and evaluate the appropriateness of the measurements generated using a data chart. Many of the professional development activities can be used directly in the classroom.

Type: Professional Development

## Student Center Activity

Students can practice answering mathematics questions on a variety of topics. With an account, students can save their work and send it to their teacher when complete.

Type: Student Center Activity

## Teaching Idea

Birds & Eggs:

In this task, students start by examining a scatter plot about the size of various bird eggs from a collection of measurements. In particular, students are asked to identify a correlation, sketch an approximation for the line of best fit, determine the equation of that line, use the equation of the line and/or the graph to make interpolative predictions, and draw conclusions about the properties of specific eggs by using the graphical presentation of the data.

Type: Teaching Idea

## Tutorial

Scatter Plots:

Scatterplots are used to visualize the relationship between two quantitative variables in a binary relation. As an example, trends in the relationship between the height and weight of a group of people could be graphed and analyzed using a scatter plot.

Type: Tutorial

## Video/Audio/Animations

Interpreting Scatter Plots - Study Time, Shoe Size, and Test Score:

This 3-minute video provides an example of how to solve a problem involving scatter plots.

Type: Video/Audio/Animation

Trend Lines (Smoking in 1945):

This 5-minute video provides an example of how to solve a problem using a trend line to estimate data through a problem called, "Smoking in 1945."

Type: Video/Audio/Animation

Fitting a Line to Data:

Khan Academy tutorial video that demonstrates with real-world data the use of Excel spreadsheet to fit a line to data and make predictions using that line.

Type: Video/Audio/Animation

## Virtual Manipulatives

Univariate and Bivariate Data:

This lesson is designed to introduce students to the difference between univariate and bivariate data, and how the two can be represented graphically. This lesson provides links to model discussions and online graphing applets, as well as suggested ways to integrate them into the lesson. Finally, the lesson provides links to follow-up lessons designed for use in succession with the current one.

Type: Virtual Manipulative

This is an online graphing utility that can be used to create box plots, bubble graphs, scatterplots, histograms, and stem-and-leaf plots.

Type: Virtual Manipulative

Curve Fitting:

With a mouse, students will drag data points (with their error bars) and watch the best-fit polynomial curve form instantly. Students can choose the type of fit: linear, quadratic, cubic, or quartic. Best fit or adjustable fit can be displayed.

Type: Virtual Manipulative

Line of Best Fit:

This manipulative allows the user to enter multiple coordinates on a grid, estimate a line of best fit, and then determine the equation for a line of best fit.

Type: Virtual Manipulative

KidsZone: Create a Graph:

Create bar, line, pie, area, and xy graphs.

Type: Virtual Manipulative

## STEM Lessons - Model Eliciting Activity

How Fast Can You Go:

Students will apply skills (making a scatter plot, finding Line of Best Fit, finding an equation and predicting the y-value of a point on the line given its x-coordinate) to a fuel efficiency problem and then consider other factors such as color, style, and horsepower when designing a new coupe vehicle.

## MFAS Formative Assessments

Bungee Cord Data:

Students are asked to construct a scatterplot corresponding to a given set of data.

Cheesy Statistics:

Students are given a scatterplot in a real-world context and asked to describe the association between the variables.

Infectious Statistics:

Students are given a scatterplot in a real-world context and asked to describe the association between the variables.

Population Density:

Students are given a scatterplot in a real-world context and asked to describe the association between the variables.

Sleepy Statistics:

Students are given a scatter plot in a real-world context and asked to describe the association between the variables.

## Original Student Tutorials Science - Grades K-8

The Notion of Motion, Part 2 - Position vs Time:

Continue an exploration of kinematics to describe linear motion by focusing on position-time measurements from the motion trial in part 1. In this interactive tutorial, you'll identify position measurements from the spark tape, analyze a scatterplot of the position-time data, calculate and interpret slope on the position-time graph, and make inferences about the dune buggy’s average speed

The Notion of Motion, Part 3 - Average Velocity:

Describe the average velocity of a dune buggy using kinematics in this interactive tutorial. You'll calculate displacement and average velocity, create and analyze a velocity vs. time scatterplot, and relate average velocity to the slope of position vs. time scatterplots.

This is part 3 of 3 in a series that mirrors inquiry-based, hands-on activities from our popular workshops.

• Click  to open The Notion of Motion, Part 1 - Time Measurements
• Click HERE to open The Notion of Motion, Part 2 - Position vs Time

## Original Student Tutorials Mathematics - Grades 6-8

Scatterplots Part 1: Graphing:

Learn how to graph bivariate data in a scatterplot in this interactive tutorial.

This is part 1 in 6-part series. Click below to open the other tutorials in the series.

Scatterplots Part 2: Patterns, Associations and Correlations:

Explore the different types of associations that can exist between bivariate data in this interactive tutorial.

This is part 2 in 6-part series. Click below to open the other tutorials in the series.

## Student Resources

Vetted resources students can use to learn the concepts and skills in this benchmark.

## Original Student Tutorials

The Notion of Motion, Part 3 - Average Velocity:

Describe the average velocity of a dune buggy using kinematics in this interactive tutorial. You'll calculate displacement and average velocity, create and analyze a velocity vs. time scatterplot, and relate average velocity to the slope of position vs. time scatterplots.

This is part 3 of 3 in a series that mirrors inquiry-based, hands-on activities from our popular workshops.

• Click  to open The Notion of Motion, Part 1 - Time Measurements
• Click HERE to open The Notion of Motion, Part 2 - Position vs Time

Type: Original Student Tutorial

The Notion of Motion, Part 2 - Position vs Time:

Continue an exploration of kinematics to describe linear motion by focusing on position-time measurements from the motion trial in part 1. In this interactive tutorial, you'll identify position measurements from the spark tape, analyze a scatterplot of the position-time data, calculate and interpret slope on the position-time graph, and make inferences about the dune buggy’s average speed

Type: Original Student Tutorial

Scatterplots Part 2: Patterns, Associations and Correlations:

Explore the different types of associations that can exist between bivariate data in this interactive tutorial.

This is part 2 in 6-part series. Click below to open the other tutorials in the series.

Type: Original Student Tutorial

Scatterplots Part 1: Graphing:

Learn how to graph bivariate data in a scatterplot in this interactive tutorial.

This is part 1 in 6-part series. Click below to open the other tutorials in the series.

Type: Original Student Tutorial

How Is the Weather?:

This task can be used as a quick assessment to see if students can make sense of a graph in the context of a real world situation. Students also have to pay attention to the scale on the vertical axis to find the correct match. The first and third graphs look very similar at first glance, but the function values are very different since the scales on the vertical axes are very different. The task could also be used to generate a group discussion on interpreting functions given by graphs.

Students are asked to examine a scatter plot and then interpret its meaning. Students should identify the form of the relationship (linear, curved, etc.), the direction or correlation (positive or negative), any specific outliers, the strength of the relationship between the two variables, and any other relevant observations.

## Student Center Activity

Students can practice answering mathematics questions on a variety of topics. With an account, students can save their work and send it to their teacher when complete.

Type: Student Center Activity

## Tutorial

Scatter Plots:

Scatterplots are used to visualize the relationship between two quantitative variables in a binary relation. As an example, trends in the relationship between the height and weight of a group of people could be graphed and analyzed using a scatter plot.

Type: Tutorial

## Video/Audio/Animations

Trend Lines (Smoking in 1945):

This 5-minute video provides an example of how to solve a problem using a trend line to estimate data through a problem called, "Smoking in 1945."

Type: Video/Audio/Animation

Fitting a Line to Data:

Khan Academy tutorial video that demonstrates with real-world data the use of Excel spreadsheet to fit a line to data and make predictions using that line.

Type: Video/Audio/Animation

## Virtual Manipulatives

This is an online graphing utility that can be used to create box plots, bubble graphs, scatterplots, histograms, and stem-and-leaf plots.

Type: Virtual Manipulative

Curve Fitting:

With a mouse, students will drag data points (with their error bars) and watch the best-fit polynomial curve form instantly. Students can choose the type of fit: linear, quadratic, cubic, or quartic. Best fit or adjustable fit can be displayed.

Type: Virtual Manipulative

Line of Best Fit:

This manipulative allows the user to enter multiple coordinates on a grid, estimate a line of best fit, and then determine the equation for a line of best fit.

Type: Virtual Manipulative

## Parent Resources

Vetted resources caregivers can use to help students learn the concepts and skills in this benchmark.

How Is the Weather?:

This task can be used as a quick assessment to see if students can make sense of a graph in the context of a real world situation. Students also have to pay attention to the scale on the vertical axis to find the correct match. The first and third graphs look very similar at first glance, but the function values are very different since the scales on the vertical axes are very different. The task could also be used to generate a group discussion on interpreting functions given by graphs.

Students are asked to examine a scatter plot and then interpret its meaning. Students should identify the form of the relationship (linear, curved, etc.), the direction or correlation (positive or negative), any specific outliers, the strength of the relationship between the two variables, and any other relevant observations.

## Teaching Idea

Birds & Eggs:

In this task, students start by examining a scatter plot about the size of various bird eggs from a collection of measurements. In particular, students are asked to identify a correlation, sketch an approximation for the line of best fit, determine the equation of that line, use the equation of the line and/or the graph to make interpolative predictions, and draw conclusions about the properties of specific eggs by using the graphical presentation of the data.

Type: Teaching Idea

## Video/Audio/Animation

Fitting a Line to Data:

Khan Academy tutorial video that demonstrates with real-world data the use of Excel spreadsheet to fit a line to data and make predictions using that line.

Type: Video/Audio/Animation