Site: US and Canada

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  
  • 3461

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  
  • 3532

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  
  • 3929

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  
  • 3829

Interpreting R2

This lesson involves predicting values of a particular variable.

Alignments  Standards  |  Textbook  
  • 3331

Influencing Regression

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

Alignments  Standards  |  Textbook  
  • 3487

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  
  • 4060

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  
  • 3333
TI-Nspire is a trademark of Texas Instruments. Adobe, Flash Player and Reader, and Microsoft Word are registered trademarks of their owners.
Version: 1.20130613.103712 rev. 47808 (Production)