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.

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Formative Assessments
Formative Assessments
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CPALMS: Students are asked to construct a scatterplot corresponding to a given set of data.

Bungee Cord Data

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

Population Density

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

Cheesy Statistics

Assessment Logo. Includes a gray clipboard on a blue background.
CPALMS: Students are given a scatterplot in a real-world context and asked to describe the association between the variables.

Sleepy Statistics

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

Infectious Statistics

Virtual/Hands-on Manipulatives
Virtual/Hands-on Manipulatives
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CPALMS: This is an online graphing utility that can be used to create box plots, bubble graphs, scatterplots, histograms, and stem-and-leaf plots

Advanced Data Grapher

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

Line of Best Fit

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CPALMS: In this activity, students are able to drag data points and watch the best-fit polynomial curve form instantly. They can choose the type of fit: linear, quadratic, cubic, or quartic. Best fit or adjustable fit can be displayed.

Curve Fitting

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CPALMS: This manipulative helps students in understanding the usefulness of scatter plots when investigating whether there is a relationship between 2 variables. They could develop a systematic plan for collecting and entering data and set appropriate ranges for the x and y scales.

Scatterplot

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CPALMS: With this resource, students are able to create, bar, line, pie, area, and xy graphs.

KidsZone: Create a Graph

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CPALMS: This resource is designed to introduce students to the difference between univariate and bivariate data, and how the two can be represented graphically. There are also links to online graphing applets and suggestions on how to integrate these into lessons.

Univariate and Bivariate Data

Assessment Questions
Assessment Questions
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Multiple Choice
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Power Point
Videos of Expert Instruction
Videos of Expert Instruction
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Shark researcher, Chip Cotton, discusses the use of regression lines, slope, and determining the strength of the models he uses in his research.
Slope and Deep Sea Sharks
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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.``
Trend Lines (Smoking in 1945)
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This 3-minute video provides an example of how to solve a problem involving scatter plots.
Interpreting Scatter Plots – Study Time, Shoe Size, and Test Score
Hook/Performance Tasks
Hook/Performance Tasks
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Illustrative Mathematics: Students create scatterplots, and think critically about associations and outliers in data as well as informally fit a trend line. By using spaghetti rather than drawing a line, students can easily make adjustments on placement of the ``line``.

Animal Brains

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Illustrative Mathematics: In this task, the student should address the form of the relationship (linear, curved, etc.), direction (positive or negative), and strength of the relationship between the two variables, and also point out any unusual observations.

Texting and Grades I

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Illustrative Mathematics: Students glean contextual information about bird eggs from a collection of measurements organized in a scatter plot. They identify correlation and use it to make interpolative predictions and reason about the properties via the graphical presentation of data.

Birds’ Eggs

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Illustrative Mathematics: Students participate with measuring hand span and height and notice specifics about the data, typically the association between these has observed to be positive, moderately strong, and linear with relatively few outliers.

Hand Span and Height