The coefficient of determination, denoted as $R^2$, is a measure of the proportion of the variance in the dependent variable (here, "grade") that is predictable from the independent variables.

From the provided output, the value of $R^2$ is given as 70.1%.

To report it as a decimal, the value is:

$R^2 = 0.701$

Thus, the correct value of the coefficient of determination is 0.701.

Would you like more details or have any questions?

Here are 5 related questions to explore further:

1. What does the adjusted $R^2$ indicate?
2. How is the degrees of freedom calculated in this context?
3. What is the difference between $R^2$ and adjusted $R^2$?
4. What does the value of $s = 2.786$ represent in the output?
5. Why is the coefficient of determination important in regression analysis?

Tip: Always compare $R^2$ and adjusted $R^2$ to understand the impact of additional predictors on the model's performance.