https://file.aiquickdraw.com/mathbot/file/1725893158585jlsjyb4x.jpg

The coefficient of determination = ____.

0.671

0.71

0.654

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.

The coefficient of determination = ____.
Options:
0.671
0.71
0.654

Learn how to determine the coefficient of determination (R^2) in linear regression. This problem illustrates the concept using real data with an R^2 value of 0.671, showcasing its significance in statistical analysis. Suitable for high school students in Grades 10-12.

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