# Statistics homework help

Simple Regression
Let’s say that we wanted to be able to predict the Braking distance in feet for a car based on its weight in pounds. Using this sample data, perform a simple-linear regression to determine the line-of-best fit. Use the Weight as your x (independent) variable and braking distance as your y (response) variable. Use 4 places after the decimal in your answer.

Answer the following questions related to this simple regression

14.  What is the equation of the line-of-best fit? Insert the values for bo and b1 from above into   y = bo + b1x.

15. What is the slope of the line? What does it tell you about the   relationship between the Weight (Pounds) and Braking distance (Feet) data? Be   sure to specify the proper units.

16. What is the y-intercept of the line? What does it tell you about the   relationship between the Weight   and Braking distance?

17. What would you predict the Braking distance   would be for a car that Weighs 2650 pounds? Show your calculation.

18. Let’s say you want to buy a muscle car that   Weighs 4250 pounds.  What effect   would you predict this would have on the braking distance of the car? Relate this to the Braking distance you   found for a car weighing 2650 pounds in the previous question.

19. Find the coefficient of determination (R2 value) for this data. What does this tell you about this   relationship?
[Hint: see   definition on Page 311.]
Part V. Multiple Regression
Let’s say that we wanted to be able to predict the city miles per gallon for a car using
· Weight in pounds
· Length in inches
· Cylinders
Using this sample data, perform a multiple-regression using Weight, Length, Cylinder, City.  Select City (Column 8) as your dependent variable.