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.

• Students will construct a scatter plot and determine a linear regression that fits the data.
• Students will calculate a correlation coefficient from data sets.
• Students will describe correlation in data sets and distinguish it from causation.

• causation
• correlation coefficient
• linear regression
• outlier

• 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.
• Students should have prior experience using the TI-Nspire handheld to create scatter plots. In addition, they should have had some discussion about correlation. Students should also know how to solve an equation using the solver.
• Notes for using the TI-Nspire™ Navigator™ System are included throughout the activity. The use of the Navigator System is not necessary for completion of this activity.