Activity Overview
Students graph scatter plots and understand the concepts of correlation and least-squares regression. They also perform transformations to achieve linearity in the data plot.
Before the Activity
Install the Statistics with List Editor application on the calculator using one of these two methods:
- TI Connect™, a TI Connectivity Cable, and the Unit-to-Unit Link Cable
- TI-Navigator™ "send to class" feature
- See the attached PDF file for detailed instructions for this activity
- Print pages 59 - 78 from the attached PDF file for your class
During the Activity
Distribute the pages to the class.
Follow the Activity procedures:
Enter the heights of buildings in Philadelphia & New York City, and the year of their completion, as lists
Set up scatter plots for both sets and compare the graphs
Enter the car name, mileage per gallon, weight of car, and number of cylinders as lists
Find the simple linear correlation coefficient between mileage and weight, mileage and cylinder, cylinder and weight
Plot the data and observe the relationship
Plot a least-squares regression line through the data
Observe that the line does not fit the data sufficiently
Identify the outliers
Plot the data without the outlier point and observe that the line is close to the regression line
Calculate the Coefficient of Determination and the sum of squares regression and linearize the data
Perform different types of transformations and measure how well the line fits the transformed data
After the Activity
Review student results:
As a class, discuss questions that appeared to be more challenging
Re-teach concepts as necessary