To find the best-fit linear regression equation, we need to calculate the slope ($m$) and intercept ($b$) of the line $y = mx + b$, where $y$ is the final grade, and $x$ is the attendance percentage.

Step-by-Step Calculation:

1. Calculate the means of the attendance percentages ($x$) and grades ($y$).

2. Calculate the slope ($m$) using the formula:

   $m = \frac{\sum (x - \bar{x})(y - \bar{y})}{\sum (x - \bar{x})^2}$

3. Calculate the intercept ($b$) using the formula:

   $b = \bar{y} - m\bar{x}$

Let's compute these values step-by-step.The best-fit linear regression equation, where attendance is the explanatory variable, is:

$y = 0.68x + 33.84$

If you have any questions or need further explanations, let me know!

Related Questions:

1. How does the slope of the regression line affect the relationship between attendance and grades?
2. What does the intercept of the regression line represent in this context?
3. How can you determine the accuracy of this regression model?
4. What would be the predicted grade for a student with 80% attendance using this model?
5. How can outliers in the data affect the linear regression equation?

Tip: The closer the slope is to zero, the weaker the relationship between the two variables.