MAFS.8.SP.1.1Archived Standard

In this 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

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

Type: Formative Assessment

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

Type: Formative Assessment

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

Type: Formative Assessment

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

Type: Formative Assessment

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

Type: Formative Assessment

This lesson is an introductory lesson to correlation coefficients. Students will engage in research prior to the teacher giving any direct instruction. The teacher will provide instruction on how to find the correlation coefficient by hand and using Excel.

Type: Lesson Plan

This lesson is an introductory lesson to correlation coefficients. Students will engage in research prior to the teacher giving any direct instruction. The teacher will provide instruction on how to find the correlation coefficient by hand and using Excel.

Type: Lesson Plan

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

Students will participate in collecting trash either on campus or another location. They will compare the distance traveled and the weight of the trash bag collected. Students will explore the use of mean and median in finding the ratios of the data set. They will discuss the use of mean and median in finding the relationship between the independent and dependent variables. Students will examine their scatter plot and determine if any patterns of association exist. They will compare their data to a coastal cleanup report. 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

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

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

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

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

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

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

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

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 5^th 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

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

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

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

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

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

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

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.

Model Eliciting Activities, MEAs, are open-ended, interdisciplinary problem-solving activities that are meant to reveal students’ thinking about the concepts embedded in realistic situations. Click here to learn more about MEAs and how they can transform your classroom.

Type: Lesson Plan

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

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

Type: Lesson Plan

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

Type: Lesson Plan

This lesson is an introductory lesson to correlation coefficients. Students will engage in research prior to the teacher giving any direct instruction. The teacher will provide instruction on how to find the correlation coefficient by hand and using Excel.

Type: Lesson Plan

In this activity, students use scatter plots to compare the estimated and actual heights of familiar celebrities and athletes. They will determine how their answers impact 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

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

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

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.

• Scatterplots Part 1: Graphing
• Scatterplots Part 3: Trend Lines
• Scatterolots Part 4: Equation of the Trend Line
• Scatterplots Part 5: Interpreting the Equation of the Trend Line
• Scatterplots Part 6: Using Linear Models

Type: Original Student Tutorial

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
• Scatterplots Part 3: Trend Lines
• Scatterolots Part 4: Equation of the Trend Line
• Scatterplots Part 5: Interpreting the Equation of the Trend Line
• Scatterplots Part 6: Using Linear Models

Type: Original Student Tutorial

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

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.

Download the CPALMS Perspectives video student note taking guide.

Type: Perspectives Video: Professional/Enthusiast

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.

Download the CPALMS Perspectives video student note taking guide.

Type: Perspectives Video: Professional/Enthusiast

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

Download the CPALMS Perspectives video student note taking guide.

Type: Perspectives Video: Professional/Enthusiast

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.

Type: Problem-Solving Task

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.

Type: Problem-Solving Task

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.

Type: Problem-Solving Task

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.

Type: Problem-Solving Task

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

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

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

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

Type: Video/Audio/Animation

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

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

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

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

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

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

Type: Virtual Manipulative