The equation of the line of best fit is:

$y = 2.5077x + 4.5538$

Would you like any additional details or explanations on how the line of best fit was calculated?

Here are some related questions to deepen your understanding:

1. How is the line of best fit useful in predicting future values?
2. What does the slope of the line represent in this context?
3. Can you explain what the y-intercept means for this dataset?
4. How would the equation change if we added more data points?
5. What is the significance of the $R^2$ value in linear regression?

Tip: The slope of a line indicates how much the dependent variable (y) changes with a unit increase in the independent variable (x).