Q5. Consider the following estimated regression equation: ROEt = 0.23 - 1.50 CEt
The standard error of the coefficient is 0.40 and the number of observations is 32. The 95% confidence interval for the slope coefficient, b1, is: A) {-2.317 < b1 < -0.683}. B) {0.683 < b1 < 2.317}. C) {-2.300 < b1 < -0.700}.
Q6. Consider the following estimated regression equation: AUTOt = 0.89 + 1.32 PIt
The standard error of the coefficient is 0.42 and the number of observations is 22. The 95% confidence interval for the slope coefficient, b1, is: A) {-0.766 < b1 < 3.406}. B) {0.444 < b1 < 2.196}. C) {0.480 < b1 < 2.160}.
Q7. Assume you ran a multiple regression to gain a better understanding of the relationship between lumber sales, housing starts, and commercial construction. The regression uses lumber sales as the dependent variable with housing starts and commercial construction as the independent variables. The results of the regression are:
| Coefficient | Standard Error | t-statistics | Intercept | 5.37 | 1.71 | 3.14 | Housing starts | 0.76 | 0.09 | 8.44 | Commercial construction | 1.25 | 0.33 | 3.78 | The level of significance for a 95% confidence level is 1.96 |
Construct a 95% confidence interval for the slope coefficient for Housing Starts. A) 0.76 ± 1.96(0.09). B) 0.76 ± 1.96(8.44). C) 1.25 ± 1.96(0.33).
Q8. Construct a 95% confidence interval for the slope coefficient for Commercial Construction. A) 1.25 ± 1.96(0.33). B) 0.76 ± 1.96(0.09). C) 1.25 ± 1.96(3.78).
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发表于 2009-1-7 13:29
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