As a sales manager of your company you decided to examine if the sales (in quant

Question

As a sales manager of your company you decided to examine if the sales (in quantity), Q, is determined by your own product price ( in dollars), P, advertisement expenditure ( in million dollars), A, and consumers average income (in 1,000 dollars), Y, you estimated a multiple regression equation of:
Q= a + bP + cA + dY where a, b, c, and d are coefficients.
The following is a partial printout of the multiple regression estimation obtained with missing values due to ink shortage:
Summary Output
Regression Statistics
Multiple R R Square Adjusted R Square Standard Error 142.44 Observations. 10 ANOVA
DF. SS. MS. F
Regression. 208 Residual. 52 Total
Based on this information the degrees of freedom for regression ( sum of squares) are ____ and that for residual ( or error sum of squares are ____.
A. 2,10 B. 2,7 C. 3,9 D. 3,6 E. 4,5

As a sales manager of your company you decided to examine if the sales (in quantity), Q, is determined by your own product price ( in dollars), P, advertisement expenditure ( in million dollars), A, and consumers average income (in 1,000 dollars), Y, you estimated a multiple regression equation of:
Q= a + bP + cA + dY where a, b, c, and d are coefficients.
The following is a partial printout of the multiple regression estimation obtained with missing values due to ink shortage:
Summary Output
Regression Statistics
Multiple R R Square Adjusted R Square Standard Error 142.44 Observations. 10 ANOVA
DF. SS. MS. F
Regression. 208 Residual. 52 Total
Based on this information the degrees of freedom for regression ( sum of squares) are ____ and that for residual ( or error sum of squares are ____.
A. 2,10 B. 2,7 C. 3,9 D. 3,6 E. 4,5

As a sales manager of your company you decided to examine if the sales (in quantity), Q, is determined by your own product price ( in dollars), P, advertisement expenditure ( in million dollars), A, and consumers average income (in 1,000 dollars), Y, you estimated a multiple regression equation of:
Q= a + bP + cA + dY where a, b, c, and d are coefficients.
The following is a partial printout of the multiple regression estimation obtained with missing values due to ink shortage:
Summary Output
Regression Statistics
Multiple R R Square Adjusted R Square Standard Error 142.44 Observations. 10 ANOVA
DF. SS. MS. F
Regression. 208 Residual. 52 Total
Based on this information the degrees of freedom for regression ( sum of squares) are ____ and that for residual ( or error sum of squares are ____.
A. 2,10 B. 2,7 C. 3,9 D. 3,6 E. 4,5

Explanation / Answer

The degrees of freedom for Regression is one less than the number of parameters being estimated. If there are n predictor variables and so there are n parameters for the coefficients on those variables. There is always one additional parameter for the constant so there are n+1 parameters. But the degree of freedom is one less than the number of parameters, so there are n+1 - 1 = n degrees of freedom. That is, the df(Regression) = # of predictor variables. In this case it is 3.

The df(Residual) is the sample size minus the number of parameters being estimated, So in this case it is 10 - 3 - 1 = 6

So the correct answer is D option.

Related Questions

Navigate

• Browse (All)
• Browse A
• Subjects

---

---

Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.