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To solve this, we need the linear equation found in part (a), which should be in the form \( y = mx + b \), where \( y \) represents the height, \( x \) represents the age, \( m \) is the slope (rate of height increase per year), and \( b \) is the y-intercept (height at age zero, theoretically).

If you can share the equation from part (a), I can substitute \( x = 3 \) to predict the height of a 3-year-old boy.

Would you like to provide the equation, or do you need help finding it in part (a)?

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If you're interested in similar problems or deeper insights, here are some related questions:

1. What is the purpose of finding a linear equation for growth prediction?
2. How do you interpret the slope in the context of this height prediction?
3. Why might linear equations sometimes not be accurate for age-related predictions?
4. What other forms of equations (besides linear) could be used for growth prediction?
5. How can data points affect the accuracy of a linear prediction model?

**Tip:** Always check the assumptions of linear growth models, as real-world data might not always follow a straight line.

Use the linear equation found in part (a) to predict the average height of a 3-year-old boy. The average height of a 3-year-old boy is ___ in.

Learn how to use a linear equation to predict the average height of a 3-year-old boy. This problem applies key algebraic concepts, including linear equations, slope-intercept form, and prediction techniques, ideal for students in Grades 7-9.

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