Lesson 22
Observing More Patterns in Scatter Plots
Lesson Narrative
In this lesson, students visually identify clusters in data and then do a card sort to distinguish linear and non-linear associations. Students will not study non-linear associations or clustering using quantitative tools. Instead they will rely on visual patterns in scatter plots (MP7). Next, they bring everything they have studied in the unit so far to analyze and interpret bivariate data in context (MP4). They create a scatter plot, identify outliers, fit a line, and determine and interpret the slope of the line. They compare actual and predicted values. They reflect on what they have learned about modeling bivariate data.
Learning Goals
Teacher Facing
- Categorize data sets, and describe (orally) the properties used to create categories.
- Create a scatter plot and draw a line to fit bivariate data, and identify (orally and in writing) outliers that appear in the data.
- Describe (orally) features of data on scatter plots, including “linear” and “nonlinear association” and “clustering” using informal language.
- Interpret (orally and in writing) features of a scatter plot with a line of fit, including outliers, slope of the line, and clustering.
Student Facing
Let’s look for other patterns in data.
Required Materials
Required Preparation
Print and cut up cards from the Scatter Plot City blackline master. Prepare 1 set of cards for every student.
Learning Targets
Student Facing
- I can analyze a set of data to determine associations between two variables.
- I can pick out clusters in data from a scatter plot.
- I can use a scatter plot to decide if two variables have a linear association.
Print Formatted Materials
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| Student Task Statements | docx | |
| Cumulative Practice Problem Set | docx | |
| Cool Down | Log In | |
| Teacher Guide | Log In | |
| Teacher Presentation Materials | docx | |
| Blackline Masters | zip |