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Statistics

Describing Bivariate Data

In these lessons, students investigate the relationship between two quantitative variables by analyzing scatterplots, outliers and influential points, correlation coefficients, and the least-squares regression line. Students create and describe graphs and identify and use the important characteristics of the graphs to better understand the relationship between the variables.

Statistics: Describing Bivariate Data Activities

Title Type

Scatterplot Pulse Rates

This lesson involves creating a scatterplot and fitting a line to student pulse rates collected before and after exercise.

Alignments  Standards  |  Textbook  
  • 3647

Monopoly and Regression

This lesson involves analyzing the association between the number of spaces from Go and the cost of the property on a standard Monopoly board.

Alignments  Standards  |  Textbook  
  • 3686

Tootsie Pops & Hand Span

Students will collect data, find the linear regression model of the data, and address aspects of the data that affect regression.

Alignments  Standards  |  Textbook  
  • 4013

Investigating Correlation

This lesson involves investigating the connection between the scatterplot of bivariate data and the numerical value of the correlation coefficient.

Alignments  Standards  |  Textbook  
  • 3971

Interpreting R2

This lesson involves predicting values of a particular variable.

Alignments  Standards  |  Textbook  
  • 3420

Influencing Regression

This lesson involves a least-squares regression line fit to a set of nine values.

Alignments  Standards  |  Textbook  
  • 3584

Influence and Outliers

In this activity, students will identify outliers that are influential with respect to the least-squares regression line. Students will describe the role of the location of a point relative to the other data in determining whether that point has influence on the least-squares regression line.

Alignments  Standards  |  Textbook  
  • 4162

Transforming Bivariate Data

This lesson involves square root, semi-log, and log-log transformations of curved bivariate data using given data sets.

Alignments  Standards  |  Textbook  
  • 3422
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