QMB 3200 Summer 2023 Homework 4
Complete your work in this document in black type. Leave the existing document in the blue type it is currently in and do not edit the document except to add your responses below each prompt. Submit your completed work to Canvas.
Part 1. Run a simple linear regression of your student data set using the price of the vehicle as the dependent variable (y) and the mileage as the independent variable (x), then answer the questions below.
a. Insert your printout. (8 points)
b. What are you trying to predict and in what units is it measured? (1 pt.)
c. What is the predictor and in what units is it measured? (1 pt.)
d. Is this model statistically useful? Why or why not? (1 pt.)
e. What is the y-intercept of the model? (1 pt.)
f. Can the y-intercept be practicallyinterpreted in this case (yes or no)? Why or why not? (1 pt.)
g. What is the slope of the model? (1 pt.)
h. What is the R²? (1 pt.)
i. How do you interpret the R²? Explicitly state what the R2 you found means. (1 pt.)
j. What is the 2s (2 x standard deviation)? Report this in the appropriate unit of measurement. (1 pt.)
k. Is this a practically useful model? Explain why or why not? Provide statistical support for your reasoning. (1 pt.)
l. Is this the best model for predicting the price of a vehicle? Why or why not? Explain what was discussed in the lecture regarding “best models.” (1 pt.)
Part 2. Find the predicted/fitted value and the intervals associated with both if you were predicting the price of a vehicle with 40,000 miles on it. Answer the questions below.
a. Insert the printout. (8 points)
b. What is the predicted/fitted value? (1 pt.)
c. Interpret the predicted interval as it was done in the lecture slides (See Lecture 7 slide 54). (1 pt.)
d. Interpret the fitted interval as it was done in the lecture slides (see Lecture 7 slide 54). (1 pt.)
