On a bit of a time crunch, could use some help :) Step 3: Analyze your data.
Now that you have represented your data graphically, it can be more easily analyzed.
Describe how the line of best fit and the correlation coefficient can be used to determine the correlation between the two variables on your graph.

Describe the type of correlation between the two variables on your graph. How do you know?

Does the correlation between the variables imply causation? Explain.

How do you calculate the residuals for a scatterplot?

Calculate the residuals for your scatterplot in step 2d.

Create a residual plot for your data.

Does your residual plot show that the linear model from the regression calculator is a good model? Explain your reasoning.

Step 4: Make a prediction with your data.
Using your equation from step 2d, estimate the GPA of a student who studies for 15 hours a week. Justify your answer.