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From the image you provided, you are given a scatter plot showing the temperature (in °F) over the course of 12 months, and a question asking which function best models the data from Month 1 to Month 9. The available choices are linear functions, and the correct answer is already indicated as:

\[ y = 2.5x + 90 \]

This means that the function \( y = 2.5x + 90 \) provides the best fit for the data points from Month 1 to Month 9. The reason for this is that the slope (2.5) suggests that the temperature increases by approximately 2.5°F per month, and the intercept (90) suggests that the temperature in Month 0 (if extended back) would be around 90°F. This matches the trend shown in the scatter plot.

Would you like further details on how to interpret the graph and why this function was the best choice? Here are 5 questions related to this topic:

1. How do you calculate the slope of a line from data points?
2. What is the significance of the y-intercept in a linear equation?
3. How can we verify the accuracy of the chosen function using specific points from the graph?
4. What method can be used to find the line of best fit if the equation is not provided?
5. How would the equation change if more months (e.g., Month 10 to 12) were included?

**Tip:** Always check the slope of the function to see if it matches the general trend (upward or downward) of the data in scatter plots!

Which function best models the data from Month 1 to Month 9?

Learn how to model temperature data using a linear function. This problem involves identifying the best fit line based on scatter plot data from Month 1 to Month 9. The correct function is y = 2.5x + 90, representing a temperature increase of 2.5°F per month. Ideal for students in Grades 9-10.

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