From the image, the coefficient of determination (denoted as $R^2$) is clearly provided as:

$R^2 = 67.1\%$

This percentage can be converted into a decimal form by dividing by 100, giving:

$R^2 = 0.671$

Therefore, the correct value for the coefficient of determination is 0.671.

Would you like a detailed explanation of how this value is interpreted or calculated?

Here are 5 related questions that can deepen your understanding:

1. What does the $R^2$ value represent in linear regression?
2. How does the adjusted $R^2$ differ from $R^2$, and why is it important?
3. What does the T-statistic indicate in regression analysis?
4. Why is the coefficient of determination important in evaluating a model's performance?
5. How do you interpret the regression equation $y = 5.22x - 13.11$ in the context of this output?

Tip: $R^2$ indicates the proportion of variance in the dependent variable explained by the independent variable(s) in the model.