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The problem is to determine the most appropriate linear model for the data shown in the scatterplot. Let’s break it down:

### Analysis:
1. **Slope (m):**
   The points in the scatterplot suggest a negative linear relationship because as \( x \) increases, \( y \) decreases.

2. **Intercept (b):**
   When \( x = 0 \), \( y \approx 10 \), which means the y-intercept is approximately 10.

3. **Correct Equation Form:**
   Given the slope is negative and the y-intercept is positive, the linear model must take the form \( y = -1.9x + 10.1 \).

### Answer:
**The correct choice is \( \mathbf{B: y = -1.9x + 10.1} \).**

Would you like a deeper explanation on how the slope and intercept are calculated? 

Here are some questions to consider for further exploration:
1. How do you determine the slope of a line from two points?
2. What is the significance of a negative slope in a linear equation?
3. How do we identify the y-intercept in a graph?
4. Why is \( y = -1.9x + 10.1 \) the best fit for this scatterplot?
5. What methods exist to compute the equation of a line from a scatterplot in real-world data?

**Tip:** When analyzing scatterplots, always look for overall trends (positive, negative, or no correlation) to narrow down the appropriate model.

Which of the following equations is the most appropriate linear model for the data shown in the scatterplot?

Discover how to choose the most appropriate linear model for a given scatterplot. Learn about slope, y-intercept, and the importance of analyzing trends in data. Suitable for students in Grades 8-10.

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