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The scatterplot provided shows the relationship between the number of traffic lights in various towns and the average weekly number of traffic light violations. There is a line of best fit plotted on the graph, which we will use to estimate the number of violations for 75 traffic lights.

### Step-by-step Explanation:

1. **Interpret the Question**: We need to estimate the average weekly number of traffic light violations for a town with 75 traffic lights, based on the line of best fit.

2. **Locate 75 Traffic Lights on the Graph**: 
   - On the x-axis (which represents the number of traffic lights), locate 75.
   
3. **Follow the Line of Best Fit**:
   - Trace vertically from 75 on the x-axis until you meet the line of best fit.
   - From that point on the line, trace horizontally to the y-axis (which represents the average weekly number of violations).
   
4. **Read the Value on the Y-axis**: 
   - Based on the line of best fit, the value corresponds to **around 55** on the y-axis.

### Answer:
The predicted average weekly number of traffic light violations in a town with 75 traffic lights is **55**.

Thus, the correct answer is:
- **C) 55**

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Would you like further details or have any other questions? Here are some related questions for you to consider:

1. How can we calculate the equation of the line of best fit?
2. What is the significance of the slope in this graph?
3. How do outliers affect the accuracy of predictions based on the line of best fit?
4. What statistical methods are used to determine a line of best fit?
5. How could the correlation between traffic lights and violations be interpreted in real-world contexts?

**Tip:** When working with scatterplots, always consider the overall trend shown by the line of best fit to make predictions, rather than focusing on individual data points.

Based on the line of best fit, which of the following is the predicted average weekly number of traffic light violations in a town with 75 traffic lights?

This problem focuses on interpreting scatterplots and using the line of best fit to predict the number of weekly traffic violations in towns with varying numbers of traffic lights. Learn how to estimate values using a linear model. Suitable for students in Grades 9-12.

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