Please quick a) 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.

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

c) Does the correlation between the variables imply causation? Explain.

d) How do you calculate the residuals for a scatterplot?

e) Calculate the residuals for your scatterplot in step 2d.

f) Create a residual plot for your data.

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

A) The line of best fit gives a general outlook on the data while the correlation is the exact points showcased to calculate or show for a data set or table.

B) Between the two variables it is a positive correlation because they both increase in the same direction. Positive correlation is a relationship between two variables in which both variables move in tandem—that is, in the same direction.

C) Not really considering the fact they are both headed in the same direction. It would if say one was increasing and the other was going in the opposite direction.

D) So, to find the residual I would subtract the predicted value from the measured value

E)

Ex: (Your first row)

9.2 - 2.23 = 6.97

^ ^ ^

Hr. GPA Difference

F) Look at my added gif 'residual-plot.gif' (I believe it's asking you to sketch or raw something like that).