Simple Regression Model Practice Problems
Chapter 4 Simple regression model Practice problems
Use Chapter 4 Powerpoint question 4.1 to answer the following questions: 1. Report the Eveiw output for regression model .
Please write down your fitted regression model.
2. Are the sign for consistent with your expectation, explain?
3. Hypothesize the sign of the coefficient and test your hypothesis at 5% significance level using t-table.
4. What percentage of variation in 30 year fixed mortgage rate is explained by this model? Why?
Use Chapter 4 Powerpoint question 4.2 to answer the following questions:
5. Report the Eveiw output for regression model
Based on the estimation period of 1986.01 – 1999.07. Please write down your fitted regression model.
6. Is Trend correlated with USPI? Set up the hypothesis testing at 5% significance level.
7. What percentage of variation in USPI is explained by this model? Why?
8. Based on your Eview model, report your forecast of USPI for the period of 1999.08-2000.07. Report RMSE.
Use Chapter 4 Powerpoint question 4.3 to answer the following questions:
9. Report the Eveiw output for regression model USPIt = (USTBR)t + t based on the estimation period of 1986.01 – 1999.07. Please write down your fitted regression model.
Dependent Variable: USPI | | | Method: Least Squares | | | Date: 01/24/11 Time: 16:46 | | | Sample: 1986M01 1999M07 | | | Included observations: 163 | | | | | | | | | | | | | | Coefficient | Std. Error | t-Statistic | Prob. | | | | | | | | | | | C | 108.2449 | 3.533589 | 30.63312 | 0.0000 | USTBR | -2.657671 | 0.632655 | -4.200821 | 0.0000 | | | | | | | | | | | R-squared | 0.098781 | Mean dependent var | 93.90615 | Adjusted R-squared | 0.093183 | S.D. dependent var | 12.25531 | S.E. of regression | 11.67035 | Akaike info criterion | 7.764174 | Sum squared resid | 21927.74 | Schwarz criterion |
Use Chapter 4 Powerpoint question 4.1 to answer the following questions: 1. Report the Eveiw output for regression model .
Please write down your fitted regression model.
2. Are the sign for consistent with your expectation, explain?
3. Hypothesize the sign of the coefficient and test your hypothesis at 5% significance level using t-table.
4. What percentage of variation in 30 year fixed mortgage rate is explained by this model? Why?
Use Chapter 4 Powerpoint question 4.2 to answer the following questions:
5. Report the Eveiw output for regression model
Based on the estimation period of 1986.01 – 1999.07. Please write down your fitted regression model.
6. Is Trend correlated with USPI? Set up the hypothesis testing at 5% significance level.
7. What percentage of variation in USPI is explained by this model? Why?
8. Based on your Eview model, report your forecast of USPI for the period of 1999.08-2000.07. Report RMSE.
Use Chapter 4 Powerpoint question 4.3 to answer the following questions:
9. Report the Eveiw output for regression model USPIt = (USTBR)t + t based on the estimation period of 1986.01 – 1999.07. Please write down your fitted regression model.
Dependent Variable: USPI | | | Method: Least Squares | | | Date: 01/24/11 Time: 16:46 | | | Sample: 1986M01 1999M07 | | | Included observations: 163 | | | | | | | | | | | | | | Coefficient | Std. Error | t-Statistic | Prob. | | | | | | | | | | | C | 108.2449 | 3.533589 | 30.63312 | 0.0000 | USTBR | -2.657671 | 0.632655 | -4.200821 | 0.0000 | | | | | | | | | | | R-squared | 0.098781 | Mean dependent var | 93.90615 | Adjusted R-squared | 0.093183 | S.D. dependent var | 12.25531 | S.E. of regression | 11.67035 | Akaike info criterion | 7.764174 | Sum squared resid | 21927.74 | Schwarz criterion |