A micro economist wants to determine how corporate sales are influenced by capital and wage. She collect the data and produced the following regression output (Table 1)

Regression Analysis

R 0.689

Adjusted R 0.662 n 26

R 0.830

Std. Error 17501.64 Dep. Var Sales

ANOVA Table

Source SS df MS F p-value

Regression 15579777040 7789888520 25.432 0.0001

Residual 7045072780 306307512

Regression Output

variables coefficients std. error t (df=28) p-value

Intercept 15800 6038.2999 2.617 0.0154

Capital 0.1245 0.2045 0.609 0.5485

Wages 7.0762 1.4729 4.804 0.0001

1. Explain the meaning of each coefficient, do their signs conform the economic theory?
2. What fraction of the variability in sales is explained by spending on capital and wages?
3. Which of the independent variables in the model are individually significant at the 5% level?
4. At the 0.01 level of significance, what conclusion should the micro economist draw regarding the inclusion of Capital in the regression model?
5. When the micro economist used a simple linear regression model with sales as the dependent variable and wages as the independent variable, he obtained an R-square value of 0.601. What additional percentage of the total variation of sales has been explained by including capital spending in the multiple regression?
6. If X1 is capital and X2 is wages, the least squares multiple regression equation for this problem is (Y is sales)
7. What is the predicted sales (in millions of dollars) for a company spending $100 million on capital and $100 million on wages?