The scatter plot shows the number of years of experience, x, and the amount charged per hour, y, for each of 25 dog sitters in California. (a) Write an approximate equation of the line of best fit for the data. It doesn't have to be the exact line of best fit. (b) Using your equation from part (a), predict the amount charged per hour by a dog sitter with 10 years of experience. Note that you can use the graphing tools to help you approximate the line. Amount charged (in dollars per hour, 22- 20- 18- 16- 14- 12- y 10+ 8+ ? (a) Write an approximate equation of the line of best y = 0.5x + 7 (b) Using your equation from part (a), predict the am charged per hour by a dog sitter with 10 years of ex $12

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**Understanding Scatter Plots: Analyzing Dog Sitters' Rates**

The **scatter plot** shows the number of years of experience, \( x \), and the amount charged per hour, \( y \), for each of 25 dog sitters in California.

(a) **Write an approximate equation of the line of best fit for the data**. It doesn't have to be the exact line of best fit.

(b) **Using your equation from part (a)**, predict the amount charged per hour by a dog sitter with 10 years of experience.

*Note: You can use the graphing tools to help you approximate the line.*

### Scatter Plot Analysis

#### Graph Description:
The scatter plot displays data points representing 25 dog sitters. The x-axis represents the "Years of experience," ranging from 0 to 22 years. The y-axis represents the "Amount charged (in dollars) per hour," ranging from $2 to $22.

#### Graph Details:
- Each point on the scatter plot shows a different dog sitter’s years of experience and corresponding hourly charge.
- A line of best fit is drawn to indicate the trend in the data.
- The line shows an upward trend, indicating that as years of experience increase, the amount charged per hour also tends to increase.

### Solution:

#### Part (a):
Write an approximate equation of the line of best fit.

**Equation:**

\[ y = 0.5x + 7 \]

This equation indicates that for every additional year of experience, the hourly charge increases by approximately $0.50. The base charge (when \( x = 0 \)) is around $7.

#### Part (b):
Using your equation from part (a), predict the amount charged per hour by a dog sitter with 10 years of experience.

**Calculation:**
Substitute \( x = 10 \) into the approximate equation:

\[ y = 0.5(10) + 7 \]
\[ y = 5 + 7 \]
\[ y = 12 \]

Thus, a dog sitter with 10 years of experience is predicted to charge **$12 per hour**.

Understanding scatter plots and lines of best fit is crucial for analyzing data trends and making predictions in various fields, including service pricing based on experience.
Transcribed Image Text:**Understanding Scatter Plots: Analyzing Dog Sitters' Rates** The **scatter plot** shows the number of years of experience, \( x \), and the amount charged per hour, \( y \), for each of 25 dog sitters in California. (a) **Write an approximate equation of the line of best fit for the data**. It doesn't have to be the exact line of best fit. (b) **Using your equation from part (a)**, predict the amount charged per hour by a dog sitter with 10 years of experience. *Note: You can use the graphing tools to help you approximate the line.* ### Scatter Plot Analysis #### Graph Description: The scatter plot displays data points representing 25 dog sitters. The x-axis represents the "Years of experience," ranging from 0 to 22 years. The y-axis represents the "Amount charged (in dollars) per hour," ranging from $2 to $22. #### Graph Details: - Each point on the scatter plot shows a different dog sitter’s years of experience and corresponding hourly charge. - A line of best fit is drawn to indicate the trend in the data. - The line shows an upward trend, indicating that as years of experience increase, the amount charged per hour also tends to increase. ### Solution: #### Part (a): Write an approximate equation of the line of best fit. **Equation:** \[ y = 0.5x + 7 \] This equation indicates that for every additional year of experience, the hourly charge increases by approximately $0.50. The base charge (when \( x = 0 \)) is around $7. #### Part (b): Using your equation from part (a), predict the amount charged per hour by a dog sitter with 10 years of experience. **Calculation:** Substitute \( x = 10 \) into the approximate equation: \[ y = 0.5(10) + 7 \] \[ y = 5 + 7 \] \[ y = 12 \] Thus, a dog sitter with 10 years of experience is predicted to charge **$12 per hour**. Understanding scatter plots and lines of best fit is crucial for analyzing data trends and making predictions in various fields, including service pricing based on experience.
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