# Simple linear regression questions

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Please answer whether these questions or true, false or uncertain. Explain the answer.

1. In a simple linear regression, the coefficient of determinations is the amount of unexplained variation divided by the total variation.

2. If a simple linear regression model's R(squared) is equal to 0.81; then the same model's r will equal 0.9.

3. The "best" fitting regression line will minimize the sum of squared total (SST).

4. A correlation between y and x of 0.9 implies that there is significant evidence to conclude that y and x are related.

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