Answer questions (a) through (e) using the following information and output for multiple regression
The production of car tires in any given year is related to the number of cars produced that year and in prior years. Suppose our econometric model resulted in the following data.
|
Regression Coefficient
|
t-Statistic
|
p-Value
|
X1 = Cars Produced This Year
|
5.00
|
10.4
|
0.0000
|
X2 = Cars Produced Last Year
|
0.25
|
0.6
|
0.5499
|
X3 = Cars Produced 2 Years Ago
|
0.67
|
1.4
|
0.1646
|
X4 = Cars Produced 3 Years Ago
|
2.12
|
2.7
|
0.0081
|
X5 = Cars Produced 4 Years Ago
|
3.44
|
6.5
|
0.0000
|
Constant
|
-50,000
|
|
|
Multiple R
|
0.83
|
|
|
R Squared
|
?
|
|
|
1. Why is the coefficient for "cars produced this year" a positive number?
2. Which is the most statistically significant variable? What evidence shows this?
3. Which is the least statistically significant variable? What evidence shows this?
4. For a 0.05 level of significance, should any variable be dropped from this model? Why or why not?
5. What is the R Squared Value? What is the interpretation?