Question 4 Suppose a multiple regression model y=B₁ + B₂ x2 + ... + BK XK + E has been estimated and the results summarized in the following analysis-of-variance (ANOVA) table. ANOVA | Degrees of freedom | Sum of squares | Mean squares Explained | 4 | 54 | 13.50 Residual | 60 | 20 | 0.333 Total | 64 | 74 | 1.156 Use the information in the table to compute the F-statistic for testing the null hypothesis that all the slope coefficients are zero? that is, that 0= B₂= ... = BK. A) F = 13.50. B F = 40.5. (C) F = 0.730. D F = 0.712. Question 5 A regression with Y (number of employees in thousands) on X1 (education spending in thousands of USD) and X2 (percentage of tax rebates) yields a coefficient on X2 to be 2.3. Which of the following would be a correct interpretation of that coefficient? A "Tax rebates would increase by 3.45% for a 1.5 thousand UDS increase in educational spending, holding all else equal." B) "The number of employees would increase by 2.3 thousand for a 1.5 percent increase in tax rebates, holding all else equal." "The number of employees would increase by 3.45 thousand for a 1.5 percentage increase in tax rebates, holding all else equal." D Tax rebates would increase by 3.45% for a 1.5 thousand UDS increase in educational spending.
Question 4 Suppose a multiple regression model y=B₁ + B₂ x2 + ... + BK XK + E has been estimated and the results summarized in the following analysis-of-variance (ANOVA) table. ANOVA | Degrees of freedom | Sum of squares | Mean squares Explained | 4 | 54 | 13.50 Residual | 60 | 20 | 0.333 Total | 64 | 74 | 1.156 Use the information in the table to compute the F-statistic for testing the null hypothesis that all the slope coefficients are zero? that is, that 0= B₂= ... = BK. A) F = 13.50. B F = 40.5. (C) F = 0.730. D F = 0.712. Question 5 A regression with Y (number of employees in thousands) on X1 (education spending in thousands of USD) and X2 (percentage of tax rebates) yields a coefficient on X2 to be 2.3. Which of the following would be a correct interpretation of that coefficient? A "Tax rebates would increase by 3.45% for a 1.5 thousand UDS increase in educational spending, holding all else equal." B) "The number of employees would increase by 2.3 thousand for a 1.5 percent increase in tax rebates, holding all else equal." "The number of employees would increase by 3.45 thousand for a 1.5 percentage increase in tax rebates, holding all else equal." D Tax rebates would increase by 3.45% for a 1.5 thousand UDS increase in educational spending.
Managerial Economics: Applications, Strategies and Tactics (MindTap Course List)
14th Edition
ISBN:9781305506381
Author:James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris
Publisher:James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris
Chapter4A: Problems In Applying The Linear Regression Model
Section: Chapter Questions
Problem 1E
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Transcribed Image Text:Question 4
Suppose a multiple regression model
y=B₁ + B₂ x2 + ... + BK XK + E
has been estimated and the results summarized in the following analysis-of-variance (ANOVA) table.
ANOVA | Degrees of freedom | Sum of squares | Mean squares
Explained | 4 | 54 | 13.50
Residual | 60 | 20 | 0.333
Total | 64 | 74 | 1.156
Use the information in the table to compute the F-statistic for testing the null hypothesis that all the slope coefficients are zero?
that is, that 0= B₂= ... = BK.
(A) F= 13.50.
B
F = 40.5.
C) F = 0.730.
F = 0.712.
Question 5
A regression with Y (number of employees in thousands) on X1 (education spending in thousands of USD) and X2 (percentage of tax
rebates) yields a coefficient on X2 to be 2.3. Which of the following would be a correct interpretation of that coefficient?
A "Tax rebates would increase by 3.45% for a 1.5 thousand UDS increase in educational spending, holding all else equal."
(B)
"The number of employees would increase by 2.3 thousand for a 1.5 percent increase in tax rebates, holding all else
equal."
"The number of employees would increase by 3.45 thousand for a 1.5 percentage increase in tax rebates, holding all
else equal."
(D) Tax rebates would increase by 3.45% for a 1.5 thousand UDS increase in educational spending.
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