Assume that you want to develop a linear model to predict the "Resale Value" of a car based on its "Price".
i. Use the least squares method to estimate the regression coefficients (You can use the mathematic formula of the book or the available tools in Excel).
ii. State the regression equation.
iii. Which coefficients are statistically significant at the 5% level?
iv. Give the interpretation of the regression coefficients b0 and b1. What is the expected Resale Value, for a car priced at 30 thousands?
v. Interpret the value of the R2.
vi. How can you improve your model?
vii. How the value of R2 is compared with the value of the correlation coefficient between "Resale Value" and "Price" found in 4.ii.
The data set is given in the file "Car Sales.xlsx". The file contains data regarding sales of different car models as well as technical characteristics of the specific cars. The description of the variables is given in the sheet Data.