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)?

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.