A linear regression was performed to find the best fit line for race distances and times of a dog named Midnight. The linear regression allows one to predict future race times based on distances. The document outlines the steps to perform a linear regression using a graphing calculator: 1) Enter the x and y variable data into lists L1 and L2, 2) generate a scatter plot of the data, 3) use the calculator's LinReg function to calculate the best fit line equation, and 4) graph the best fit line to visualize the linear relationship between distances and times.

1. BY: KATE ALBERTINI AND KATIE FAIRMAN How to do a Linear Reggression

2. Why should I do a Linear Regression? A linear regression will give you a best fit line that enables you to predict points future outcomes of a scenario. In this scenario, we will show a linear regression for the race distances and times for the dog, Midnight.

3. Starting your Linear Regression First on your calculator, go to Y= Highlight Plot 1 at the top of your screen by pressing Enter Next press Stat and hit 1: Edit Enter your x values into L1 and your y values into L2

4. Your screen will now look like this:

5. How to see the scatter plot of your data Press Window Then set the x min to 0 and the x max to 20 Also set the y min to 0 and the y max to 5 This is to insure all the points in the data fit in the screen Hit Graph

6. A view of your scatter plot

7. How to calculate the Best Fit Line Press Stat Hike over to Calc at the top of your screen Press 4: LinReg(ax+b) Now press Enter

8. Your screen will now look like this:

9. Graphing the Best Fit Line Press Y= Plug in the linear regression model that you just calculated Now press Graph to see the graph of the Best Fit Line

10. TA-DAAAA!!

11. Congratulations! You’ve made your Linear Regression Now you are able to plug in different distances for x and predict how fast Midnight will be able to race the distance!