The manager of a second-hand car dealership is interested in the relationship between the selling price of a car and the number of years since it was originally sold. They take data on 32 cars of the same make and define the following variables:

Y = Selling price of the car (in thousands)

X = The age of the car (in years)

A simple regression model of the form:

Price = b₀ +b₁Age + e

was estimated and an excerpt from the output is shown below.

Selling Price 70 y = -1.944x + 58.707 60 . ... RZ = 0.8025 50 . . . . . . . . 40 Selling Price (Thousands $) . .. . ... ....................... .... ......... 30 20 10 O 0 5 10 15 20 Age (Years) SUMMARY OUTPUT Regression Statistics Multiple R 0.895815 R Square 0.802484 Adjusted R Square 0.7959 Standard Error 5.622182 Observations 32 ANOVA df SS MS F Significance F Regression 1 3852.701 3852.701 121.88647 4.34803E-12 Residual 30 948.2679 31.60893 Total 31 4800.969 Coefficientsandard Err t Stat P-value Lower 95% Intercept 58.70745 1.889279 31.074 0 54.84903211 Age -1.94397 0.176081 -11.0402 0 -2.303572003