A large automobile manufacturer wants to study the relationship between weight (in lbs) and the variability in braking distance (in feet) on a dry surface for eight of their automobiles. The following data was collected.

Weight, x - 5940, 5340, 6500, 5100, 5850, 4800, 5600, 5890

Variability in Braking Distance, y - 1.78, 1.93, 1.91, 1.59, 1.66, 1.50, 1.61, 1.70

Note: based on the above values, the first automobile has a weight of 5940 lbs and a variability in braking distance of 1.78 feet for a dry surface.

1a. Conduct a simple linear regression in Excel and share your results.

1b. Does weight appear to be a good predictor? Why or why not?

1c. What is the R-squared value and what does it tell you?

1d. What is the regression equation (i.e., the model)?

1e. What is the predicted variability in braking distance for a weight of 6,000 lbs.

1f. What other factors (independent variables) could affect braking distance?