Consider the following computer output from a multiple regression analysis relating the cost of car insurance to the variables: number of car accidents, driver's credit score, and safety rating of the car. Intercept Car Accidents (In last 3 years) Credit Score Safety Rating Answer Coefficients 1278 230.04 Coefficients Does the sign of the coefficient for the variable safety rating make sense? -140.58 328.63 Standard Error 129.86 23.23 14.97 397.29 t Stat 9.841 P-value 0.0000 9.903 0.0000 -9.391 0.0000 0.827 0.4117 O No, because it is expected that as the safety rating increases then the cost should decrease. O Yes, because it is expected that as the safety rating increases then the cost should decrease. O No, because it is expected that as the safety rating increases then the cost should also increase. O Yes, because it is expected that as the safety rating increases then the cost should also increase. Tables Keypad Keyboard Shortcuts
Consider the following computer output from a multiple regression analysis relating the cost of car insurance to the variables: number of car accidents, driver's credit score, and safety rating of the car. Intercept Car Accidents (In last 3 years) Credit Score Safety Rating Answer Coefficients 1278 230.04 Coefficients Does the sign of the coefficient for the variable safety rating make sense? -140.58 328.63 Standard Error 129.86 23.23 14.97 397.29 t Stat 9.841 P-value 0.0000 9.903 0.0000 -9.391 0.0000 0.827 0.4117 O No, because it is expected that as the safety rating increases then the cost should decrease. O Yes, because it is expected that as the safety rating increases then the cost should decrease. O No, because it is expected that as the safety rating increases then the cost should also increase. O Yes, because it is expected that as the safety rating increases then the cost should also increase. Tables Keypad Keyboard Shortcuts
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Transcribed Image Text:**Understanding Multiple Regression Analysis: Car Insurance Cost**
Consider the following analysis output from a multiple regression model. This model relates the cost of car insurance to variables such as the number of car accidents, driver's credit score, and the safety rating of the car.
| **Coefficients** | **Coefficients** | **Standard Error** | **t Stat** | **P-value** |
|------------------------|------------------|--------------------|------------|-------------|
| **Intercept** | 1278 | 129.86 | 9.841 | 0.0000 |
| **Car Accidents (In last 3 years)** | 230.04 | 23.23 | 9.903 | 0.0000 |
| **Credit Score** | -140.58 | 14.97 | -9.391 | 0.0000 |
| **Safety Rating** | 328.63 | 397.29 | 0.827 | 0.4117 |
**Analysis:**
- **Intercept (1278):** Represents the base cost of car insurance without considering other variables.
- **Car Accidents (230.04):** A positive coefficient indicates that more accidents increase insurance costs, with a statistically significant P-value of 0.0000.
- **Credit Score (-140.58):** A negative coefficient suggests higher credit scores decrease costs, also highly significant statistically.
- **Safety Rating (328.63):** Although the coefficient is positive, the high P-value (0.4117) implies it is not statistically significant, which questions its impact on cost.
**Question:**
Does the sign of the coefficient for the variable safety rating make sense?
**Answer Options:**
- ○ No, because it is expected that as the safety rating increases then the cost should decrease.
- ○ Yes, because it is expected that as the safety rating increases then the cost should decrease.
- ○ No, because it is expected that as the safety rating increases then the cost should also increase.
- ○ Yes, because it is expected that as the safety rating increases then the cost should also increase.
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