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Students combine their knowledge of linear functions with knowledge of data representations and analysis to make the jump from univariate data in one variable to bivariate data in two variables.
In Unit 8, eighth-grade students make the jump from univariate data in one variable to bivariate data in two variables. They re-engage in the major work of the grade, analyzing scatterplots for positive or negative linear trends (MP.7), using lines to represent relationships between the variables, writing linear equations, interpreting these equations in context (MP.2), and using the equations to make predictions beyond the scope of the data (MP.4). Throughout the unit, students analyze scatterplots and two-way tables for trends in the data, asking themselves, Is there evidence in this graph or table to suggest an association between the variables? (MP.2)
Prior to eighth grade, students explored how and why data is collected—by thinking about statistical questions, samples, populations, and various ways to analyze data representations. Students worked with line plots, histograms, and box plots, and they considered what the shape, center, and spread of these data sets said about the data itself.
In high school, students’ understanding of statistics is formalized. They analyze bivariate data using functions, design and carry out experiments, and make predictions about outcomes based on probabilities. Students use their knowledge of association between variables as a basis for correlation. They develop nonlinear models for data and formally analyze how closely the model fits the data.
Pacing: 12 instructional days (9 lessons, 2 flex days, 1 assessment day)
For guidance on adjusting the pacing for the 2020-2021 school year due to school closures, see our 8th Grade Scope and Sequence Recommended Adjustments.
This assessment accompanies Unit 8 and should be given on the suggested assessment day or after completing the unit.
|Double bar graph||
|Segmented bar graph||
line fit to data
double bar graph
segmented bar graph
Define bivariate data. Analyze data in scatter plots.
Create scatter plots for data sets and make observations about the data.
Identify and describe associations in scatter plots including linear/nonlinear associations, positive/negative associations, clusters, and outliers.
Informally fit a line to data. Judge the fit of the line and make predictions about the data based on the line.
Write equations to represent lines fit to data and make predictions based on the line.
Interpret the slope and $$y$$-intercept of a fitted line in context.
Key: Major Cluster Supporting Cluster Additional Cluster