https://file.aiquickdraw.com/mathbot/file/1727371536191wo6xk327.jpg

The problem presented in the image includes a scatterplot showing the relationship between the number of traffic lights and the average weekly number of traffic light violations across various towns. A line of best fit is drawn through the points to approximate this relationship. 

The question asks for the predicted average weekly number of traffic light violations in a town with 75 traffic lights, based on the line of best fit.

### Steps to Solve:

1. **Interpret the Graph**: 
   - The x-axis represents the "Number of traffic lights."
   - The y-axis represents the "Average weekly number of traffic light violations."

2. **Locate 75 Traffic Lights on the Graph**:
   - Look at 75 on the x-axis.
   - Trace upwards until you hit the line of best fit.

3. **Read the Corresponding Value on the y-Axis**:
   - From the point where 75 on the x-axis intersects the line of best fit, trace horizontally to the y-axis. The approximate y-value (average weekly violations) seems to be around 55.

4. **Choose the Correct Answer**:
   - Based on the graph, the closest value is **55**, which corresponds to option **C**.

Thus, the predicted average weekly number of traffic light violations for a town with 75 traffic lights is **C) 55**.

### Questions:
1. How do we calculate the slope of the line of best fit?
2. What are scatterplots used for in statistical analysis?
3. What is the importance of the line of best fit in predicting values?
4. How can the correlation between two variables be determined from a scatterplot?
5. What other types of relationships might we see in scatterplots (e.g., non-linear)?

**Tip:** When reading scatterplots, always focus on the general trend and how closely the points follow the line of best fit to assess the strength of the correlation.

Learn how to predict the average weekly traffic light violations in a town with 75 traffic lights using a scatterplot and the line of best fit. The problem covers key concepts like interpreting scatterplots and using the line equation y = mx + b for estimation. Suitable for students in Grades 8-10.

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