The data in the table represent the number of licensed drivers in various age groups and the number of fatal accidents within the age group by gender. Complete parts (a) through (c) below. O Click the icon to view the data table. (a) Find the least-squares regression line for males treating the number of licensed drivers as the explanatory variable, x, and the number of fatal crashes, y, as the response variable. Repeat this procedure for females. Find the least-squares regression line for males. Data for licensed drivers by age and gender. (Round the x coefficient to three decimal places as needed. Round the constant to the nearest integer as needed.) Find the least-squares regression line for females. Number of Number Number of Male Fatal (Round the x coefficient to three decimal places as needed. Round the constant to the nearest integer as needed.) Number of Female Fatal Licensed Drivers (000s) Licensed Drivers Crashes Crashes (b) Interpret the slope of the least-squares regression line for each gender, if appropriate. How might an insurance company use this information? Age (000s) (Male) (Female) < 16 12 227 12 77 What is the correct interpretation of the slope of the least-squares regression line for males? Select the correct choice below and, if necessary, fill in the answer box to complete your (Use the answer from part a to find this answer.) 16-20 6,424 6,973 5,180 6,139 6,816 17,664 20,077 19,984 2,113 21-24 5,016 1,521 O A. If the average age of all male licensed drivers increases by 1, then the number of fatal crashes increases by. on average. O B. If the number of male licensed drivers increases by 1 (thousand), then the number of fatal crashes increases by, on average. 25-34 18,068 8,540 2,780 35-44 20,406 7,990 2,742 45-54 19,898 7,111 2,285 14,441 8,405 O C. If the number of fatal crashes increases by 1, then the number of male licensed drivers increases by thousand, on average. 55-64 14,353 4,527 1,514 65-74 8,194 2,274 938 O D. It does not make sense to interpret the slope. >74 4,803 2,022 5,375 969 What is the correct interpretation of the slope of the least-squares regression line for females? Select the correct choice below and, if necessary, fill in the answer box to complete you (Use the answer from part a to find this answer.) O A. If the average age of all female licensed drivers increases by 1, then the number of fatal crashes increases by, on average. Print Done O B. If the number of female licensed drivers increases by 1 (thousand), then the number of fatal crashes increases by, on average. O C. If the number of fatal crashes increases by 1, then the number of female licensed drivers increases by thousand, on average. O D. It does not make sense to interpret the slope.

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Chapter1: Starting With Matlab
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The data represents the number of licensed drivers in various age groups and the number of fatal accidents within each group by gender. You are tasked with completing several parts related to statistical analysis of this data.

(a) **Find the least-squares regression line for males.**
- Treat the number of licensed drivers as the explanatory variable, \(x\), and the number of fatal crashes, \(y\), as the response variable.
- Repeat this procedure for females.

**Regression Line Equations:**
- For males: \( \hat{y} = \Box x + \Box \) 
- Round the \(x\) coefficient to three decimal places and the constant to the nearest integer.

- For females: \( \hat{y} = \Box x + \Box \) 
- Round the \(x\) coefficient to three decimal places and the constant to the nearest integer.

(b) **Interpret the slope of the least-squares regression line for each gender.**
- Explain how an insurance company might use this information.

For males:
1. If the average age of all male licensed drivers increases by 1, then the number of fatal crashes increases by \(\Box\), on average.
2. If the number of male licensed drivers increases by 1 (thousand), then the number of fatal crashes increases by \(\Box\), on average.
3. If the number of fatal crashes increases by 1, then the number of male licensed drivers increases by \(\Box\) thousand, on average.
4. It does not make sense to interpret the slope.

For females:
1. If the average age of all female licensed drivers increases by 1, then the number of fatal crashes increases by \(\Box\), on average.
2. If the number of female licensed drivers increases by 1 (thousand), then the number of fatal crashes increases by \(\Box\), on average.
3. If the number of fatal crashes increases by 1, then the number of female licensed drivers increases by \(\Box\) thousand, on average.
4. It does not make sense to interpret the slope.

**Graph Explanation:**

The table shown in the inset provides data for licensed drivers categorized by age and gender. The columns are structured as follows:
- **Age**: Different age ranges.
- **Number of Male Licensed Drivers (000s)**
- **Number of Fatal Crashes (Male)**
- **Number of Female Licensed Drivers
Transcribed Image Text:The data represents the number of licensed drivers in various age groups and the number of fatal accidents within each group by gender. You are tasked with completing several parts related to statistical analysis of this data. (a) **Find the least-squares regression line for males.** - Treat the number of licensed drivers as the explanatory variable, \(x\), and the number of fatal crashes, \(y\), as the response variable. - Repeat this procedure for females. **Regression Line Equations:** - For males: \( \hat{y} = \Box x + \Box \) - Round the \(x\) coefficient to three decimal places and the constant to the nearest integer. - For females: \( \hat{y} = \Box x + \Box \) - Round the \(x\) coefficient to three decimal places and the constant to the nearest integer. (b) **Interpret the slope of the least-squares regression line for each gender.** - Explain how an insurance company might use this information. For males: 1. If the average age of all male licensed drivers increases by 1, then the number of fatal crashes increases by \(\Box\), on average. 2. If the number of male licensed drivers increases by 1 (thousand), then the number of fatal crashes increases by \(\Box\), on average. 3. If the number of fatal crashes increases by 1, then the number of male licensed drivers increases by \(\Box\) thousand, on average. 4. It does not make sense to interpret the slope. For females: 1. If the average age of all female licensed drivers increases by 1, then the number of fatal crashes increases by \(\Box\), on average. 2. If the number of female licensed drivers increases by 1 (thousand), then the number of fatal crashes increases by \(\Box\), on average. 3. If the number of fatal crashes increases by 1, then the number of female licensed drivers increases by \(\Box\) thousand, on average. 4. It does not make sense to interpret the slope. **Graph Explanation:** The table shown in the inset provides data for licensed drivers categorized by age and gender. The columns are structured as follows: - **Age**: Different age ranges. - **Number of Male Licensed Drivers (000s)** - **Number of Fatal Crashes (Male)** - **Number of Female Licensed Drivers
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