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The problem asks to predict the resting heart rate for a patient weighing 210 pounds using the line of best fit from the scatterplot.

### Steps:
1. **Examine the Line of Best Fit**: From the graph, the line of best fit suggests an increasing trend between weight and resting heart rate.
   
2. **Estimate from the Scatterplot**: The scatterplot data spans weights from 160 to 190 pounds, and we need to predict for 210 pounds, which is beyond the plotted range. The line of best fit at 190 pounds gives a heart rate slightly below 78 beats per minute (bpm).

3. **Extrapolate for 210 Pounds**: Since the trend is increasing, the heart rate at 210 pounds will likely be higher than 78 bpm. A reasonable estimate based on the slope suggests a predicted heart rate slightly above 80 bpm.

### Conclusion:
The closest predicted resting heart rate for a patient weighing 210 pounds would be around **80 beats per minute**.

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Would you like a more detailed explanation, or have any questions about this? 

Here are 5 related questions you might find interesting:
1. How can you calculate the exact equation of the line of best fit?
2. What is extrapolation, and how is it used in predictions?
3. How does weight generally affect resting heart rate according to research?
4. What are common methods to calculate resting heart rates?
5. How accurate are predictions based on lines of best fit in real-life data?

**Tip**: Always ensure when extrapolating beyond the data range that the relationship holds true for those values, as predictions can become less accurate.

Based on the line of best fit, which of the following is closest to the predicted resting heart rate of a ninth patient weighing 210 pounds?

Learn how to predict the resting heart rate for a patient weighing 210 pounds using the line of best fit from a scatterplot. Understand the relationship between weight and heart rate through linear regression and extrapolation. Suitable for Grades 8-10.

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