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Consider the following computer output from a multiple regression analysis relating the price of a used car to the variables: age of car, mileage, and safety rating. Intercept Age (Year) Mileage (in Thousands) Safety Rating Does the sign of the coefficient for the variable age make sense? Answer Coefficients 15068.49 -1917.82 -224.93 Coefficients 620.02 Standard Error 1951.90 250.14 16.99 69.20 t Stat 7.720 -7.667 P-value 0.0000 0.0000 -13.236 0.0000 8.960 0.0000 O No, because it is expected that as age increases then the price should also increase. O Yes, because it is expected that as age increases then the price should decrease. O No, because it is expected that as age increases then the price should decrease. O Yes, because it is expected that as age increases then the Tables Ke Keyboard She

Consider the following computer output from a multiple regression analysis relating the price of a used car to the variables: age of car, mileage, and safety rating. Intercept Age (Year) Mileage (in Thousands) Safety Rating Does the sign of the coefficient for the variable age make sense? Answer Coefficients 15068.49 -1917.82 -224.93 Coefficients 620.02 Standard Error 1951.90 250.14 16.99 69.20 t Stat 7.720 -7.667 P-value 0.0000 0.0000 -13.236 0.0000 8.960 0.0000 O No, because it is expected that as age increases then the price should also increase. O Yes, because it is expected that as age increases then the price should decrease. O No, because it is expected that as age increases then the price should decrease. O Yes, because it is expected that as age increases then the Tables Ke Keyboard She

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
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### Multiple Regression Analysis of Used Car Prices Consider the following computer output from a multiple regression analysis, which relates the price of a used car to the variables: age of car, mileage, and safety rating. #### Coefficients Table | | Coefficients | Standard Error | t Stat | P-value | |----------------|--------------|----------------|--------|---------| | **Intercept** | 15068.49 | 1951.90 | 7.720 | 0.0000 | | **Age (Year)** | -1917.82 | 250.14 | -7.667 | 0.0000 | | **Mileage (in Thousands)** | -224.93 | 16.99 | -13.236| 0.0000 | | **Safety Rating** | 620.02 | 69.20 | 8.960 | 0.0000 | #### Explanation The table above shows the results of a multiple regression analysis. Each row represents a variable included in the model, while columns display key statistics: - **Coefficients**: The estimated change in the dependent variable (car price) for a one-unit change in the independent variable, holding other variables constant. - **Standard Error**: Measures the standard deviation of the coefficient estimate. - **t Stat**: Tests whether the coefficient is statistically different from zero. - **P-value**: Indicates the probability that the coefficient is different from zero due to random chance. A p-value below 0.05 typically suggests statistical significance. #### Analysis Question Does the sign of the coefficient for the variable age make sense? **Answer Options:** - ○ No, because it is expected that as age increases, the price should also increase. - ○ Yes, because it is expected that as age increases, the price should decrease. - ○ No, because it is expected that as age increases, the price should decrease. - ○ Yes, because it is expected that as age increases, the price should also increase. Please select the option that you believe correctly interprets the relationship between car age and price.
Transcribed Image Text:### Multiple Regression Analysis of Used Car Prices Consider the following computer output from a multiple regression analysis, which relates the price of a used car to the variables: age of car, mileage, and safety rating. #### Coefficients Table | | Coefficients | Standard Error | t Stat | P-value | |----------------|--------------|----------------|--------|---------| | **Intercept** | 15068.49 | 1951.90 | 7.720 | 0.0000 | | **Age (Year)** | -1917.82 | 250.14 | -7.667 | 0.0000 | | **Mileage (in Thousands)** | -224.93 | 16.99 | -13.236| 0.0000 | | **Safety Rating** | 620.02 | 69.20 | 8.960 | 0.0000 | #### Explanation The table above shows the results of a multiple regression analysis. Each row represents a variable included in the model, while columns display key statistics: - **Coefficients**: The estimated change in the dependent variable (car price) for a one-unit change in the independent variable, holding other variables constant. - **Standard Error**: Measures the standard deviation of the coefficient estimate. - **t Stat**: Tests whether the coefficient is statistically different from zero. - **P-value**: Indicates the probability that the coefficient is different from zero due to random chance. A p-value below 0.05 typically suggests statistical significance. #### Analysis Question Does the sign of the coefficient for the variable age make sense? **Answer Options:** - ○ No, because it is expected that as age increases, the price should also increase. - ○ Yes, because it is expected that as age increases, the price should decrease. - ○ No, because it is expected that as age increases, the price should decrease. - ○ Yes, because it is expected that as age increases, the price should also increase. Please select the option that you believe correctly interprets the relationship between car age and price.
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