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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

Square it Up!

Students investigate the method of least squares by adding the squares to a scatter plot and moving a line to find the minimum sum. Then they compare their line to the built-in linear regression model.

Alignments  Standards  |  Textbook  
  • 2177

Does a Correlation Exist?

In this activity, students will determine, by examining a graph, if a data set has a positive or negative correlation coefficient. Then, they will find the linear regression equation and calculate the correlation coefficient. They will use this line to predict the value of y for a given x and vice-versa. Finally, students will investigate the effect of outliers and influential points on the regression equation and correlation coefficient.

Alignments  Standards  |  Textbook  
  • 2368

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  
  • 3841

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  
  • 3928

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  
  • 4157

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  
  • 4168

Interpreting R2

This lesson involves predicting values of a particular variable.

Alignments  Standards  |  Textbook  
  • 3541

Influencing Regression

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

Alignments  Standards  |  Textbook  
  • 3713

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  
  • 4287

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  
  • 3544
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